Machine Learning & Data Mining Algorithms
Automated Tests, Repeatable Experiments, Meaningful Results
not logged in
-
login
|
register
Results of JRS'12 Contest published, winners announced ... Results of JRS'12 Contest published, winners announced ... Results of JRS'12 Contest published, winners announced ... Results of JRS'12 Contest published, winners announced ... Results of JRS'12 Contest published, winners announced ... Results of JRS'12 Contest published, winners announced ... Results of JRS'12 Contest published, winners announced ... Results of JRS'12 Contest published, winners announced ...
Home
About Us
Contact Us
In Media
Research
Repository
Knowledge Base
TunedTester
Challenges
List
Create
About
Outsourcing
Wiki
Blog
Forum
Repository
/
StatLib
/
numeric
/
mhsets_monthly-hankou.arff
Back
Name:
Owner:
Access:
Size:
Modified:
StatLib/numeric/mhsets_monthly-hankou.arff
StatLib
public
65.4 KB
2009-11-10 12:57:23
No file description
File contents
% MHSETS % % TIME SERIES DATA SETS FOR HIPEL AND MCLEOD BOOK: % % Contents % INSTALLATION % REFERENCE % CONTACTS % VERSIONS % OVERVIEW OF THE DATASETS % FORMAT OF THE DATASETS % SCOPE OF THE BOOK % DECISION SUPPORT SYSTEM % USING THE DATASETS WITH S/SPLUS % SUMMARY OF THE SUBDIRECTORIES OF MHSETS % SUBDIRECTORY README FILES % % INSTALLATION % Copy the file mhsets.sh or mhsets.zip to an empty subdirectory mhsets. % Then type the command "sh mhsets.sh" or "pkunzip -d mhsets.zip". % % REFERENCE % K.W. Hipel and A.I. McLeod (1994), "Time Series Modelling of Water % Resources and Environmental Systems" published by Elsevier, % Amsterdam. ISBN 0-444-89270-2. (1013 pages). % % CONTACTS % A. Ian McLeod % Department of Statistical and Actuarial Sciences % The University of Western Ontario % London, Ontario, Canada N6A 5B9 % Phone: (519)661-3611 % Fax: (519)661-3813 % e-mail: aim@uwo.ca % Keith W. Hipel % Department of Systems Design Engineering % University of Waterloo % Waterloo, Ontario, Canada N2L 3G1 % Phone: (519)885-1211 ext.4644 or 2830 % Fax: (519)746-4791 % e-mail: kwhipel@sysoffice.watstar.uwaterloo.ca % % VERSIONS % This is version 1.0. % It is intended to maintain updates and/or corrections to these datasets. % These updates and corrections are available by anonymous ftp from % fisher.stats.uwo.ca in the directory pub/mhsets. % Both shar (for unix) and zip (for PC) archives are available by % anonymous ftp from fisher.stats.uwo.ca in the directory pub/mhsets. % % OVERVIEW OF THE DATASETS % The datasets provided include many of the datasets dicussed in our % book, Hipel and McLeod (1994). In our book we also mention a number of % case studies conducted by ourselves as well as other researchers. Many of % these datasets are also available here too. Other datasets which are % suitable for use in the problems which accompany the book or for % time series researchers wishing to compare their methodology to % other interesting types of data. In our time series and systems % courses, the datasets provided here are a useful and extensive % source of both classroom demonstrations and student projects and % assignments. % All datasets are in the public domain. % % FORMAT OF THE DATASETS % The data sets are organized in a number of subdirectories. Some of % subdirectories refer to particular case studies such as ASKEW and NOAKES % while other subdirectories group datasets of a similar type such as ANNUAL % and ECOLOGY. % Each dataset consists of a title plus a time series in free-format in % chronlogical order reading across. The extension .1 or .2 means that there % is one or two data series on the file. Sometimes there are additional % comments located immediately after the title. These comments are indicated % by a symbol # in column 1 of the file. This format is read directly % by our MHTS decision support package. For convenience of S or S-plus % users, a S function is provided to input these datasets into S or S-plus. % See the section, USING THE DATASETS WITH S/SPLUS, below. % % % SCOPE OF THE BOOK % This unique book provides a comprehensive presentation of the theory and % practice of time series modelling of environmental systems. % Recent and useful developments in time series analysis, stochastic hydrology % and statistical water quality modelling are combined in a coherent and % systematic manner in order to produce this landmark book on time series % methods in environmetrics. % The rich variety of time series models that are clearly defined, % explained and illustrated include ARMA, nonstationary ARIMA, % long memory FARMA, seasonal ARIMA, deseasonalized, periodic, % transfer function) noise, intervention and multivariate ARMA models. % Extensive hydrological, water quality and other environmental applications % are given for clearly demonstrating how the various kinds of time series % models can be systematically and conveniently fitted to real world data sets % by following the identification, estimation and diagnostic check stages of % model construction. Moreover, a major emphasis of the book is the use of % exploratory data analysis graphs, intervention analysis, nonparametric % trend tests and regression analysis in the detection and estimation of % trends in environmental impact assessment studies. % Other topics in environmetrics covered in the book include % time series analysis in decision making, estimating missing observations, % simulation, the Hurst phenomenon, forecasting experiments and causality. % % Professionals working in fields overlapping with environmetrics who will % find this book to be an indispensable resource include water resources % engineers, environmental scientists, hydrologists, geophysicists, % geographers, earth scientists and planners. % However, because the time series methods presented in the book can be % applied to data sets arising in fields outside of the environmental areas % described in the book, other professionals such as systems scientists, % economists, mechanical engineers, chemical engineers, and management % scientists will benefit from a knowledge of the impressive array of ideas % given in the book. % Within each professional group, the book is designed for use by teachers, % students, researchers, practitioners and consultants. % When employed for teaching purposes, this book can be used as a course text % at the upper undergraduate and graduate levels. % The only mathematical background required of the reader is a one % semester introductory course on probability and statistics. % Depending upon the number of topics covered, the book can be utilized in a % one ortwo semester course. % % DECISION SUPPORT SYSTEM % The McLeod - Hipel Time Series (MHTS) constitutes a comprehensive decision % support system for performing extensive data analyses using many of the % time series models, graphical procedures, trend tests and other techniques % described in the aforementioned book and elsewhere. % To obtain information about the MHTS package, kindly contact A. I. McLeod % (aim@uwo.ca) or K. W. Hipel (519) 885-1211. % % USING THE DATASETS WITH S/SPLUS % An S function is provided for inputing the datasets into S/Splus. % The source code is in the file readmhts.s and S style documentation % is available in readmhts.d. These two files are included in the % archive directly under the main subdirectory mhsets. % To read this function into S/Splus: source("readmhts.s") % Then to read in a particular dataset, say amazon.2, into the S variable, % z enter: z_readmhts("annual/amazon.2") % % SUMMARY OF THE SUBDIRECTORIES OF MHSETS % % ANNUAL miscellanous annual time series % ASKEW case study: monthly riverflows % ASTATKIE case study: daily riverflows % BARACOS case study: daily riverflow in arctic % BLOWFLY case study of blowfly populations % BOXJENK some classic time series % CNELSON case study: annual U.S. economic series % COMMOD some commodity prices, daily % ECOLOGY animal abundance, annual % EPI outbreaks of measles, mumps, chickenpox % HTONG case study: daily riverflows % HURST case study: long annual geophysical time series % KORSAN case study: long financial time series % LAMARCHE case study: treerings and meteorological series % LONDONWQ case study: water consumption in London, Ontario % MISC miscellaneous time series % MONTHLY miscellaneous monthly geophysical time series % NOAKES case study: monthly riverflow time series % PROTHERO case study: quarterly macro-economic series % PRUSCHA case study: annual temperature data % ROBERTS miscellaneous time series % SANFRAN case study: riverflow and meteorological series % THOMPSTO case study: quarter-monthly flows, precipitation % WISCONSI case study: employment data from Wisconsin % % % SUBDIRECTORY README FILES % % ANNUAL % Miscellaneous annual time series. % Brief Summary Of The Data Files In The Directory mhsets/annual % 1. AMAZON.2 % Amazon, High and Low Water Levels, 1962-78 % #High and Low levels of the Amazon at Iquitos, Peru, 1962-78 % #References: % #Gentry and Lopeq-Parodi (1980) "Deforestation and increased flooding in % # the upper Amazon". Science, 210, 1354-1356. % #Ramsey (1988). "The Slug Trace", The American Statistician, V.42, p.290. % % 2. BIRTHS.1 % Births per 10,000 of 23 year old women, U.S., 1917-1975 % % 3. BWATER.1 % BALTIMORE CITY ANNUAL WATER USE, 1885-1968, LITRES PER CAPITA PER DAY % % 4. CANFIRE.1 % No. of acres burned in forest fires in CANADA (excl. Yukon & NWT) 1918-1988 % % 5. CIG.3 % #CAN.Cigarette Consumption/adult, Real Price and Income/adult, 1953-75 % % 6. CORN.2 % Annual corn yield and rainfall in US cornbelt states, 1890-1927 % % 7. DAL.1 % DAL RIVER, NEAR NORSLUND,SWEDEN, 1852-1922 % % 8. DANUBE.1 % DANUBE RIVER, AT ORSHAVA,ROMANIA, 1837-1957 % % 9. DVI.1 % VOLCANIC DUST VEIL INDEX, NORTHERN HEMISPHERE, 1500-1969 % % 10. ELECUS.1 % Total Electricity Consumption, U.S., 1920-70, Kilowatt-hours (millions) % % 11. FORTALEZ.1 % Annual rainfall (mm) at Fortaleza, Brazil, 1849-1979 % #Refeference: P.A. Morettin, A.R. Mesquita, J.G.C. Rocha, % # "Rainfall at Fortaleza in Brazil Revisted" % # Time Series Analysis, Theory and Practice, Vol. 6 % # pp. 67--85. Editor: O.D. Anderson % % 12. FRNCHA.1 % FRENCH BROAD RIVER AT ASHEVILLE, N.C. % % 13. FRNCHB.1 % FRENCH BROAD RIVER NEAR NEWPORT, TENN. % % 14. GEODUCK.1 % Geoduck Clam Data, 1907-1980, interventions at t=13 and t=56 % #Reference: D.J. Noakes and A. Campbell (1992), % #"Use of Geoduck Clams to Indicate Changes in the Marine Environment % #of Ladysmith Harbour, British Columbia", Environmetircs, % #Vol. 3, No. 1, 81--97 % % 15. GLOBTP.1 % Changes In Global Temperature, Annual, 1880-1985 % #Surface air "temperature change" for the globe, 1880-1985. % #Degrees Celsius. "Temperature change" actually means temperature % #against an arbitrary zero point. % #From James Hansen and Sergej Lebedeff, "Global Trends of Measured % #Surface Air Temperature", `Journal of Geophysical Research`, Vol. 92, % #No. D11, pages 13,345-13,372, November 20, 1987. % % 16. GOTA.1 % GOTA RIVER, NEAR SJOTOP-VANNERSBURG,SWEDEN, 1807-1957 % % 17. HURON.1 % Lake Huron, mean level, July, 1860-1986 % #Mean July average water surface elevation, in feet, IGLD (1955) % #for Harbor Beach, Michigan, on Lake Huron, Station 5014. 1860--1986. % #Source: Great Lakes Water Levels, 1860-1986. U.S. Dept. of Commerce, % #National Oceanic and Atmospheric Administration, National Ocean Survey. % % 18. KIEWA.1 % KIEWA RIVER, AT KIEWA,VICTORIA, 1885-1954 % % 19. MCKEN.1 % MCKENZIE RIVER AT MCKENZIE BRIDGE, OREGON, 1911-57, cfs % % 20. MINIMUM.1 % Annual Minimum Level of Nile River, 622-1921 % % 21. MSTOUIS.1 % MISSISSIPPI RIVER, NEAR ST.LOUIS,MO., 1861-1957 % % 22. NEUMUNAS.1 % NEUMUNAS RIVER, AT SMALININKAI,LITUANIA,USSR, 1811-1943 % % 23. NILE.1 % AVERAGE ANNUAL RIVERFLOW, NILE AT ASWAN, 1870-1945 % % 24. NILE2.1 % Mean annual Nile flow, 1871-1970, units: 10^8 m^3, water yr: july-june % #Original Data Listing: % #78Biomtrka65 243- 252 % # George W. Cobb % # The problem of the Nile: Conditional solution to a changepoint problem % # % #Additional Reference: % #91EnvrMtrc 2 341- 375 % # I. B. MacNeill;S. M. Tang;V. K. Jandhyala % # A search for the source of the Nile's change-points % % 25. NYWATER.1 % NEW YORK CITY ANNUAL WATER USE, 1898-1968, LITRES PER CAPITA PER DAY % % 26. OGDEN.1 % ST. LAWRENCE RIVER AT OGDENSBURG, N.Y., 1860-1957, YEARLY FLOW % % 27. PEAS.1 % PRECIPITATION IN MM., EASTPORT, USA, 1887-1950 % % 28. PGREATL.1 % Annual precipitation, 1900-1986, Entire Great Lakes % #Annual precipitation in inches % #SOURCE: Great Lake Wate Levels U.S Dept o Commerce NOO % #- NOS Rockville MD an U.S Lak Survey Detroit MI--U.S % #Armu Corp % % 29. RHINE.1 % RHINE RIVER, NEAR BASLE,SWITZERLAND, 1807-1957 % % 30. SPIRITS.3 % Alcohol Demand, UK, 1870-1938. logs: Q(demand),P(r.price),Y(r.income) % #empirical demand function for alcoholic spirits, U.K., 1870-1938 % #source: Durbin & Watson (1951, Table 1) Biometrika, V.38, pp.159-78 % #"Testing for serial correlation in least squares regression II" % # % # spirits = log consumption per head % # income = log real income per head % # price = log real price % # % # spirits, income, price % % 31. SUNSPOTS.1 % Annual sunspot numbers, 1700-1988 % % 32. SUNSPT.1 % Annual sunspot numbers, 1700-1988 % % 33. THAMES.1 % THAMES RIVER, NEAR TEDDINGTON,ENGLAND, 1883-1954 % % 34. TPYR.1 % AVERAGE ANNUAL TEMPERATURE, CENTRAL ENGLAND, 1723-1970 % % 35. USM1.1 % M1, U.S. 1959.1-1992.2 % % 36. USM2.1 % M2, U.S. 1959.1-1992.2 % % 37. USM3.1 % M3, U.S. 1959.1-1992.2 % % 38. WHEAT.1 % Beveridge wheat price index, 1500-1869 % ---------------------------------------------------------------------------- % % ASKEW % These 26 monthly riverflow sequences were selected by Askew et al. (1971) % for their study in critical period statistics. Askew et al. (1977) % state these series represent unregulated riverflows. % Addtional Reference: Askew, A.J.,Yeh, W.W.G and Hall, W.A. (1971) % "A comparative study of critical drought simulation", Water Resources % Research 7, pp.52-62. % Brief Summary Of The Data Files In The Directory mhsets/askew % 1. ASKEW.1 % SACRAMENTO RIVER AT KESWICK, CALIFORNIA, OCTOBER 1939 - SEPTEMBER 1960 % % 2. ASKEW10.1 % CLEARWATER RIVER AT KAMIAH, IDAHO 1911 TO 1965 % % 3. ASKEW11.1 % JUDITH RIVER NEAR UTICA, MT. 1920 TO 1960 % % 4. ASKEW12.1 % MADISON RIVER NEAR WEST YELLOWSTONE, MT. 1923 TO 1960 % % 5. ASKEW13.1 % WHITEROCKS RIVER NEAR WHITEROCKS, UTAH, 1930 TO 1960 % % 6. ASKEW14.1 % MIDDLE BOULDER CREEK AT NEDERLAND, CO. 1912 TO 1960 % % 7. ASKEW15.1 % SOUTH PLATTE RIVER BELOW CHEESMAN LAKE, CO. 1925 TO 1960 % % 8. ASKEW16.1 % NECHES RIVER NEAR ROCKLAND, TEXAS 1914 TO 1960 % % 9. ASKEW17.1 % BIG FORD RIVER AT BIG FALLS, MN., 1929 TO 1960 % % 10. ASKEW18.1 % SKUNK RIVER AT AUGUSTA, IOWA 1915 TO 1960 % % 11. ASKEW19.1 % CURRENT RIVER AT VAN BUREN, MO 1922 TO 1960 % % 12. ASKEW2.1 % TRINITY RIVER AT LEWISTON, CALIFORNIA, OCTOBER 1912 - SEPTEMBER 1960 % % 13. ASKEW20.1 % WOLF RIVER AT NEW LONDON, WI 1914 TO 1960 % % 14. ASKEW21.1 % MAD RIVER NEAR SPRINGFIELD, OH. 1915 TO 1960 % % 15. ASKEW22.1 % WEST BRANCH DELAWARE RIVER AT HALE EDDY, NY 1916 TO 1960 % % 16. ASKEW23.1 % PEMIGEWASSET RIVER AT PLYMOUTH, NH 1904 TO 1960 % % 17. ASKEW24.1 % RAPPAHANNOCK RIVER NEAR FREDERICKSBURG, VA 1911 TO 1960 % % 18. ASKEW25.1 % JAMES RIVER AT BUCHANAN, VA 1911 TO 1960 % % 19. ASKEW26.1 % OOSTANAULA RIVER AT RESACA, GA 1893 TO 1960 % % 20. ASKEW3.1 % FEATHER RIVER AT OROVILLE, CALIFORNIA, OCTOBER 1902 - SEPTEMBER 1977 % % 21. ASKEW4.1 % AMERICAN RIVER AT FAIR OAKS, CALIFORNIA, OCTOBER 1906 - SEPTEMBER 1960 % % 22. ASKEW5.1 % EEL RIVER ABOVE DOS RIOS, CALIFORNIA, OCTOBER 1952 - SEPTEMBER 1960 % % 23. ASKEW6.1 % ROCK CREEK AT LITTLE ROUND VALLEY, NR. BISHOP, CALIFORNIA, SEPTEMBER 1960 % % 24. ASKEW7.1 % MCKENZIE RIVER AT MCKENZIE BRIDGE, OREGON, OCTOBER 1911 TO SEPTEMBER 1960 % % 25. ASKEW8.1 % S.F. SKYKOMISH RIVER NEAR INDEX, WASHINGTON,OCTOBER 1923 TO SEPTEMBER 1960 % % 26. ASKEW9.1 % BOISE RIVER NEAR TWIN SPRINGS, IDAHO,OCTOBER 1912 TO SEPTEMBER 1960 % ---------------------------------------------------------------------------- % % ASTATKIE % This data was compiled from published meteorological data by Tessema % Astatkie and used for nonlinear time series modelling in his Ph.D. % Thesis, Queens University (1994) "Modulated Threshold Time Series % Models". (D. Watts and E.Watt faculty advisors). % The units for flow are cms (cubic meters per second). % The units for temperature are degrees Celsius % The units for precipitation are in mm. % Acknowledgment: I would like to thank Tessema Astatkie for sending % this data to me via e-mail. % Brief Summary Of The Data Files In The Directory mhsets/astatkie % % 1. FISHER.1 % Mean daily flow, cms, Fisher River near Dallas, Jan 1 1988 - Dec 31 1991 % #Station number 05SD003 % #Latitude 51-21 N % #Longitude 97-30 W % % 2. FISHERP.1 % Total daily precipitation, mm, Jan 1 1988 - Dec 31 1991, Fisher Basin % #Station Name: Hodgson 2 % #Latitude: 51-11 N % #Longitude: 97-27 W % % 3. FISHERT.1 % Mean daily temperature, deg C, Jan 1 1988 - Dec 31 1991 % #Station Name: Hodgson 2 % #Latitude: 51-11 N % #Longitude: 97-27 W % % 4. OLDMAN.1 % Oldman River near Brocket, mean daily flow, cms, Jan 1 1988 - Dec 31 1991 % #Station Number: 05AA024 % #Latitude: 49-33 N % #Longitude: 113-49 W % % 5. OLDMANP.1 % Precipitation, mm, Jan 1 1988 - Dec 31 1991, Oldman River basin % #Station Name: Pincher Creek (Jan 1, 1988 - Aug 31 1989 and Jan 1 1900 - % # Dec 31 1991) % # Latitude: 49-31 N % # Longitude: 114-00 W % # % # Lethbridge A (Sept 1 1989 - Dec 31 1989) % # Latitude: 49-38 N % # Longitude: 112-48 W % % 6. OLDMANT.1 % Mean daily temperature, C, Jan 1 1988 - Dec 31 1991, Oldman basin % #Station Name: Pincher Creek (Jan 1, 1988 - Aug 31 1989 and Jan 1 1900 - % # Dec 31 1991) % # Latitude: 49-31 N % # Longitude: 114-00 W % # % # Lethbridge A (Sept 1 1989 - Dec 31 1989) % # Latitude: 49-38 N % # Longitude: 112-48 W % % 7. SAUGEEN.1 % Mean daily flow, cms, Saugeen River near Port Elgin, Jan 1 1988 - Dec 31 1991 % #Station number: 02FC001 % % 8. SAUGEENP.1 % Precipitation, mm, Jan 1 1988 - Dec 31 1991, Saugeen basin % #Station Name: Paisley % #Station Number: 6126210 % #Longitude: 44-16 N % #Latitude: 81-22 W % % 9. SAUGEENT.1 % Mean daily temperature, C, Jan 1 1988 - Dec 31 1991, Saugeen basin % #Station Name: Paisley % #Station Number: 6126210 % #Longitude: 44-16 N % #Latitude: 81-22 W % % % BARACOS % Some of the data used in "Modeling hydrologic time series from the Arctic" % by P.C. Baracos, K.W. Hipel & A.I. McLeod (1981), Water Resources Bulletin, % Vol. 17, No.3, pp.414-422. % Brief Summary Of The Data Files In The Directory mhsets/baracos % 1. CMINEF.1 % TREE RIVER,10QA001, 1969-76, MEAN MONTHLY FLOW % % 2. CMINER.1 % COPPERMINE, 2200900, MONTHLY, RAIN (MM), 1933-76 % % 3. CMINET.1 % COPPERMINE MONTHLY TEMPERATURE,2200900 CELSIUS,1933-1976 % ---------------------------------------------------------------------------- % % BLOWFLY % Time series data on a population of sheep blow-flies maintained % under stable conditions for two years (361 observations) collected % by A.J. Nicholson and modelled by D.R. Brillinger, J. Guckenheimer, % P. Guttorp and G. Oster (1980), "Empirical Modelling of Population % Time Series Data: The Case of Age and Density Dependent Vital Rates", % Lectures on Mathematics in the Life Sciences, Vol. 13, pp.65--90 % Brief Summary Of The Data Files In The Directory mhsets/blowfly % % 1. DEATHS.1 % deaths in total adult population % % 2. EGGS.1 % number of blowfly eggs % % 3. EMERGING.1 % number of emerging eggs % % 4. NONEMERG.1 % number of nonemerging eggs % % 5. TOTAL.1 % total blowfly population % ---------------------------------------------------------------------------- % % BOXJENK % Selected "classic" time series from Box and Jenkins (1976), % Time Series Analysis: forecasting and control. % Brief Summary Of The Data Files In The Directory mhsets/boxjenk % 1. SERIESA.1 % SERIES A, CHEMICAL PROCESS CONCENTRATION READINGS % #every 2 hours % % 2. SERIESB.1 % SERIES B, IBM STOCK PRICES % #closing price of common stock, daily, May 17 1961 to November 2 1962 % #May 17 = 137th day % % 3. SERIESB2.1 % IBM STOCK PRICES, 2ND SERIES % #closing price of common stock, daily, June 29 1959 to June 30 1960 % #June 29 = 180th day % % 4. SERIESC.1 % SERIES C, CHEMICAL PROCESS TEMPERATURE READINGS % #every minute % % 5. SERIESD.1 % SERIES D, CHEMICAL PROCESS VISCOSITY READINGS % #every hour % % 6. SERIESE.1 % SERIES E, WOLFER SUNSPOT NUMBERS, 1770-1869 % % 7. SERIESF.1 % SERIES F, SUCCESSIVE YIELDS OF BATCH PROCESS % % 8. SERIESG.1 % SERIES G, MONTHLY INTERNATIONAL AIRLINE PASSENGERS % #unit: thousands of passengers; January 1949 to December 1960 % % 9. SERIESJ.2 % SERIES J, GAS INPUT DATA, 396 VALUES % #sampling interval 9 seconds % #output = % CO_2 in outlet gas % #input = 0.60 - 0.40(input gas rate in cu. ft. / min.) % % 10. SERIESJX.1 % SERIES J, INPUT % #sampling interval 9 seconds % #input = 0.60 - 0.40(input gas rate in cu. ft. / min.) % % 11. SERIESJY.1 % SERIES J, OUTPUT % #sampling interval 9 seconds % #output = % CO_2 in outlet gas % ---------------------------------------------------------------------------- % % CNELSON % THE DATA SET WAS USED IN 'TRENDS AND RANDOM WALKS IN % MACROECONOMIC TIME SERIES; SOME EVIDENCE AND IMPLICATIONS' % BY CHARLES R. NELSON AND CHARLES I. PLOSSER PUBLISHED IN % JOURNAL OF MONETARY ECONOMICS 10 (1982) P 139-162. % NORTH HOLLAND PUBLISHING COMPANY % Acknowledgment: I would like to thank Charles Nelson for sending % this data to me via e-mail. % % Brief Summary Of The Data Files In The Directory mhsets/cnelson % % 1. BND.1 % Bond yield, U.S., 1900-1970, annual % % 2. CPI.1 % CPI, U.S., 1860-1970, annual % % 3. EMP.1 % Employment, U.S., 1860-1970, annual % % 4. GNP.1 % Nominal GNP, U.S., 1909-1970, annual % % 5. IP.1 % Industrial production, U.S., 1860-1970, annual % % 6. M.1 % Money Stock, U.S., 1889-1970, annual % % 7. PCRGNP.1 % Real per capita GNP, U.S., 1909-1970, annual % % 8. PRGNP.1 % GNP deflator, U.S., 1909-1970, annual % % 9. RGNP.1 % Real GNP, U.S., 1909-1970, annual % % 10. RWG.1 % Real wages, U.S., 1900-1970, annual % % 11. SP500.1 % Common stock prices, U.S., 1871-1970, annual % % 12. UN.1 % Employment, U.S., 1860-1970, annual % % 13. VEL.1 % Velocity of money, 1869-1970, annual % % 14. WG.1 % Wages, U.S., 1900-1970, annual % ---------------------------------------------------------------------------- % % COMMOD % This is a file of actual commodity prices of the five % commodities (feeder cattle, gold price, porkbellies, % soybeans and U.S. treasury bills) on the Chicago % market over a period of about 97-100 consecutive trading days. % For each commodity there are 3 files containing the % daily high, daily low, and daily close price. % % Brief Summary Of The Data Files In The Directory mhsets/commod % % 1. FEED.1 % FEEDER CATTLE CONTRACTS, CLOSE PRICE ON 95 CONSECUTIVE TRADING DAYS % % 2. FEEDH.1 % FEEDER CATTLE APR,81, HIGH % % 3. FEEDL.1 % FEEDER CATTLE APR,81, LOW % % 4. GOLD.1 % GOLD CLOSE PRICE, 97 SUCCESSIVE TRADING DAYS % % 5. GOLDH.1 % GOLD JUN,81, HIGH % % 6. GOLDL.1 % GOLD JUN,81, LOW % % 7. PORK.1 % PORKBELLIES, 99 CONSECUTIVE TRADING DAYS, CLOSE PRICE % % 8. PORKH.1 % PORK BELLIES, HIGH % % 9. PORKL.1 % PORK BELLIES MAR,81, LOW % % 10. SOY.1 % SOYBEAN CONTRACTS, CLOSE PRICE ON 99 CONSECUTIVE TRADING DAYS % % 11. SOYH.1 % SOYBEANS, HIGH % % 12. SOYL.1 % SOYBEANS, LOW % % 13. US.1 % U.S. TREASURY BILL CONTRACTS, 100 CONSECUTIVE TRADING DAYS % % 14. USH.1 % U.S. T BILLS, HIGH % % 15. USL.1 % U.S. TREASURY BILLS MAR,81, LOW % ---------------------------------------------------------------------------- % % ECOLOGY % Time series data on the abundance of various wild animals. Typically % these data show strong cyclically behaviour which has been the subject % for speculation and study. Basically there are two types of counts - % fur production and fur sales. The difference is that fur sales as % a one year lag over fur production. The type is indicated in the time % series title string. % % FOX DATASETS: arctic.1, hbco.1, hebron.1, hopedale.1, nain.1, okak.1 % These are from C. Elton (1942) "Voles, Mice and Lemmings", % Oxford Univ. Press. % % LYNX DATASET: % Annual Number of Lynx Trapped, MacKenzie River, 1821-1934 % Original Source: Elton, C. and Nicholson, M. (1942) % "The ten year cycle in numbers of Canadian lynx", % J. Animal Ecology, Vol. 11, 215--244. % This is the famous data set which has been listed before in % various publications: % Cambell, M.J. and Walker, A.M. (1977) "A survey of statistical work on % the MacKenzie River series of annual Canadian lynx trappings for the years % 1821-1934 with a new analysis", J.Roy.Statistical Soc. A 140, 432--436. % % FUR-SALES DATASETS: marten.1, mink.1, muskrat.1, otter_l.1, racoon.1, % skunk.1, wolf.1, wolveren.1 % These datasets are from: % Jones, J.W. (1914) "Fur-farming in Canada", Commission of Conservation % Canada, pp.209--214 % % ADDTIONAL REFERENCES: % 85JTimSrAn 6 171- 180 % Timo Teraesvirta % Mink and muskrat interaction: A structural analysis % ARIMA model;Canonical form;Time series;Transfer function % 78ApplStat27 168- 175 % W.-Y. T. Chan;Kenneth F. Wallis % Multiple time series modelling: Another look at the mink-muskrat interaction % Animal populations;Predator-prey;Autoregressive-moving average;Box-Jenkins;Identification % 75PIBiomC 8 55- 72 % G. M. Jenkins % The interaction between the muskrat and mink cycles in north Canada % 77Ststcian26 51- 75 % O. D. Anderson % A Box-Jenkens analysis of the coloured fox data from Nain, Labrador % % % Brief Summary Of The Data Files In The Directory mhsets/ecology % % 1. ARCTIC.1 % Arctic foxes, fur returns, Ungava District, 1868-1924 % #Source: C. Elton (1942) "Voles, Mice and Lemmings", Oxford Univ. Press % #Table 51, p.415-6. % % 2. HBCO.1 % Coloured fox fur returns, H.B. Co, Ungava District, 1868-1924 % #Source: C. Elton (1942) "Voles, Mice and Lemmings", Oxford Univ. Press % #Table 53, p.422 % % 3. HEBRON.1 % Coloured fox fur production, Hebron, Labrador, 1834-1925 % #Source: C. Elton (1942) "Voles, Mice and Lemmings", Oxford Univ. Press % #Table 17, p.265--266 % #remark: missing value for 1852, ie. observation no. 18 % % 4. HOPEDALE.1 % Coloured fox fur production, HOPEDALE, Labrador,, 1834-1925 % #Source: C. Elton (1942) "Voles, Mice and Lemmings", Oxford Univ. Press % #Table 17, p.265--266 % % 5. LYNX.1 % Annual Number of Lynx Trapped, MacKenzie River, 1821-1934 % #Original Source: Elton, C. and Nicholson, M. (1942) % #"The ten year cycle in numbers of Canadian lynx", % #J. Animal Ecology, Vol. 11, 215--244. % #This is the famous data set which has been listed before in % #various publications: % #Cambell, M.J. and Walker, A.M. (1977) "A survey of statistical work on % #the MacKenzie River series of annual Canadian lynx trappings for the years % #1821-1934 with a new analysis", J.Roy.Statistical Soc. A 140, 432--436. % % 6. MARTEN.1 % Fur sales, marten, HB Co., 1850-1911 % #Jones, J.W. (1914) "Fur-farming in Canada", Commission of Conservation % #Canada, pp.209--214 % % 7. MINK.1 % Fur sales, mink, HB Co., 1850-1911 % #Jones, J.W. (1914) "Fur-farming in Canada", Commission of Conservation % #Canada, pp.209--214 % % 8. MUSKRAT.1 % Fur sales, HB Co., muskrat, 1850-1911 % #Jones, J.W. (1914) "Fur-farming in Canada", Commission of Conservation % #Canada, pp.209--214 % % 9. NAIN.1 % Coloured fox fur production, Nain, Labrador, 1834-1925 % #Source: C. Elton (1942) "Voles, Mice and Lemmings", Oxford Univ. Press % #Table 17, p.265--266 % #remark: missing value for 1852, ie. observation no. 18 % % 10. OKAK.1 % Coloured fox fur production, Okak, Labrador, 1834-1925 % #Source: C. Elton (1942) "Voles, Mice and Lemmings", Oxford Univ. Press % #Table 17, p.265--266 % #remark: missing value for 1852, ie. observation no. 18 % % 11. OTTER_L.1 % Fur sales, otter (land), HB Co., 1850-1911 % #Jones, J.W. (1914) "Fur-farming in Canada", Commission of Conservation % #Canada, pp.209--214 % % 12. RACOON.1 % Fur sales, HB Co., racoon, 1850-1911 % #Jones, J.W. (1914) "Fur-farming in Canada", Commission of Conservation % #Canada, pp.209--214 % % 13. SKUNK.1 % Fur sales, H.B. Co., skunk, 1850-1911 % #Jones, J.W. (1914) "Fur-farming in Canada", Commission of Conservation % #Canada, pp.209--214 % % 14. WOLF.1 % Fur sales, HB Co., wolf, 1850-1911 % #Jones, J.W. (1914) "Fur-farming in Canada", Commission of Conservation % #Canada, pp.209--214 % % 15. WOLVEREN.1 % Fur sales, HB Co., wolferene, 1850-1911 % #Jones, J.W. (1914) "Fur-farming in Canada", Commission of Conservation % #Canada, pp.209--214 % ---------------------------------------------------------------------------- % % EPI % ORIGINAL DATA SOURCE: % Yorke, J.A. and London, W.P. (1973) % "Recurrent Outbreaks of Measles, Chickenpox and Mumps", % American Journal of Epidemiology, Vol. 98, pp.469 % % REMARKS: % Schaffer and Kot (1985) have studied this data using a nonlinear % dynamical systems approach. However traditional time series methods % are adequate. Which is better? % % REFERENCE: % Schaffer, W.M. and Kot, M. (1985) % "Nearly one dimensional dynamics in an epidemic", % Journal of Theoretical Biology, Vol. 112, pp.403--427. % % Brief Summary Of The Data Files In The Directory mhsets/epi % % 1. CHICKNYC.1 % Reported Number of Cases of Chickenpox, Monthly, 1931-1972, New York City % % 2. MEASLBAL.1 % Reported Number of Cases of Measles, Monthly, Jan. 1939- June 1972, Baltimore % % 3. MEASLNYC.1 % Reported monthly cases of measles, 1928-1972, New York City % % 4. MUMPS.1 % Reported monthly cases of mumps, 1928-197 2 New York City % ---------------------------------------------------------------------------- % % HTONG % These datasets were introduced into the literature in a paper by % Tong, Thanoon and Gudmundsson (1985) and has been used by various % nonlinear modelers since then. These datasets given in the book % by Tong (1991). For additional references, see below. % % References: % Astatkie, T. (1994), "Modulated Threshold Time Series Models". % Ph.D. Thesis, Queens University. % % Chen, R. & Tsay, R. (1993). Nonlinear additive ARX models. % Journal of the American Statistical Association, Vol. 88, pp.955-67. % % Lewis, P.A.W. (1994). Forthcoming paper in Water Resources Bulletin % % Tong, H., Thanoon, B. & Gudmundsson, G. (1985) "Threshold time % series modelling of two Icelandic riverflow systems", Water % Resources Bulletin, Vol. 21, No. 4, pp.651--661. % % Brief Summary Of The Data Files In The Directory mhsets/htong % % 1. JOKULSA.1 % Jokulsa Eystri River, mean daily flow, Jan. 1, 1972 - Dec. 31, 1974, cms % % 2. PRECIP.1 % Daily precipitation, in mm, Hveravellir, Jan. 1, 1972 - Dec. 31, 1974 % % 3. TEMPER.1 % Mean daily temperature, in deg C, Hveravellir, Jan. 1, 1972 - Dec. 31, 1974 % % 4. VATNSD.1 % Vatnsdalsa River, mean daily flow, Jan. 1, 1972 - Dec. 31, 1974, cms % ---------------------------------------------------------------------------- % % HURST % Datasets from K.W. Hipel and A.I. McLeod (1978) "Preservation of the % Rescaled Adjusted Range", Water Resources Research, Vol. 14, pp. 491-- % 517. In our paper we examined the long memory hypothesis and found % that on the whole there was no evidence for this hypothesis. % % Brief Summary Of The Data Files In The Directory mhsets/hurst % % 1. BIGCONE.1 % BIG CONE SPRUCE,SOUTHERN CALIFORNIA, U.S.A., 1458-1966, 509 VALUES % % 2. BRYCE.1 % PONDEROSA PINE,BRYCE WATER CANYON,UTAH,U.S.A., 1340-1964, 625 YEARS % % 3. DANUBE.1 % DANUBE RIVER, AT ORSHAVA,ROMANIA, 1837-1957 % % 4. DELL.1 % LIMBER PINE, DELL,MONTANA,U.S.A., 1311-1965, 655 YEARS % % 5. EAGLECOL.1 % DOUGLAS FIR,EAGLE,COLORADO, U.S.A.,M 1107-1964, 858 YEARS % % 6. ESPANOLA.1 % MUD VARVE DATA, SWEDISH TIME SCALE, ESPANOLA, CANADA, -204 TO -908, 668 YEARS % % 7. EXSHAW.1 % DOUGLAS FIR,EXSHAW,ALBERTA,CANADA, 1460-1965, 506 YEARS % % 8. GOTA.1 % GOTA RIVER, NEAR SJOTOP-VANNERSBURG,SWEDEN, 1807-1957 % % 9. LAKEVIEW.1 % PONDEROSA PINE,LAKEVIEW OREGON,U.S.A., 1421-1964, 544 YEARS % % 10. MINIMUM.1 % Annual Minimum Level of Nile River, 622-1469 % % 11. MSTOUIS.1 % MISSISSIPPI RIVER, NEAR ST.LOUIS,MO., 1861-1957 % % 12. NARAMATA.1 % PONDEROSA PINE, NARAMATA,BRITISH COLUMBIA,CANADA,1951-1965, 515 YEARS % % 13. NAVAJO.1 % DOUGLAS FIR,NAVAJO NATIONAL MONUMENT(BETATAKIN),ARIZONA,U.S.A., 700 YEARS % % 14. NEUMUNAS.1 % NEUMUNAS RIVER, AT SMALININKAI,LITUANIA,USSR, 1811-1943 % % 15. NINEMILE.1 % DOUGLAS FIR,NINE MILE CANYON (HIGH),UTHAH,U.S.A.,1194-1964, 771 YEARS % % 16. OGDEN.1 % ST. LAWRENCE RIVER AT OGDENSBURG, N.Y., 1860-1957, YEARLY FLOW % % 17. PRECIP.1 % Total annual rainfall, inches, London, England, 1813-1912 % % 18. RHINE.1 % RHINE RIVER, NEAR BASLE,SWITZERLAND, 1807-1957 % % 19. SNAKE.1 % DOUGLAS FIR,SNAKE RIVER BASIN,U.S.A.,1282-1950, 669 YEARS % % 20. SUNSPT.1 % YEARLY SUNSPOT-RELATIVE NUMBERS 1700-1960 % % 21. TEMPER.1 % AVERAGE ANNUAL TEMPERATURE, CENTRAL ENGLAND, 1723-1970 % % 22. TIOGA.1 % JEFFREY PINE,TIOGA PASS, CALIFORNIA, U.S.A., 1304-1964, 661 YEARS % % 23. WHITEMTN.1 % BRISTLECONE PINE, WHITE MOUNTAINS, CALIFORNIA,U.S.A., 800-1963, 1164 YEARS % ---------------------------------------------------------------------------- % % KORSAN % Financial time series from "Fractals and Time Series Analysis" by % R.J. Korsan (1993), Mathematica, Vol.3, pp.39-47 % % Brief Summary Of The Data Files In The Directory mhsets/korsan % % 1. DAILYIBM.1 % Daily closing price of IBM stock, Jan 1, 1980 to Oct. 8, 1992 % % 2. DAILYSAP.1 % Daily S&P 500 index of stocks, Jan. 1, 1980 to Oct. 8, 1992 % ---------------------------------------------------------------------------- % % LAMARCHE % This data was kindly provided by the late V.C. LaMarche, Jr and is the data % used in the paper by Fritts, H.C. et al. (1971) "Multivariate techniques % for specifying tree-growth and climatic relationships and for reconstructing % anomalies in Paleoclimate. Journal of Applied Meteorology, 10, pp.845-864. % The data was produced and assembled at the Tree Ring Laboratory at the % University of Arizona, Tuscon. % % The data can also be studied using Granger causality methods as in W.K. Li % (1981) "Topics in Time Series Modelling", Ch. 8, Ph.D. Thesis, University % of Western Ontario. % % Brief Summary Of The Data Files In The Directory mhsets/lamarche % % 1. CAMPITO.1 % CAMPITO MNT. TREE RING DATA, N=5405 FROM 3435BC TO 1969AD (IN .01 MM) % % 2. PRECIP.1 % Mean monthly precipitation, 1907-1972 % % 3. RING.1 % Campito treerings, 1907-1960 % % 4. TEMPER.1 % Mean monthly temperature, 1907-1972 % ---------------------------------------------------------------------------- % % LONDONWQ % The water consumption data and the number of consumers are obtained % by meter readers. Approximately half of all consumers have their meter % read in a given month. The data for residential water consumption % is the consumption for those residential consumers who had their meter % read in the given month for the last two months. This is considered % a proxy variable for the total residential water consumption. % % Prior to January 1991 the rates for residential water consumption in the % city of London were based on a descending block structure. % So the more water one used, the cheaper the rate. % For example in 1983, the first 200 cubic feet were % charged at $3.80 per 100 cubic feet, the next 50000 cubic feet were charged % at $0.64 per cubic feet; % and the remainder was charged at $0.53 per cubic feet. % In January of 1991 the billing was changed to encourage conservation. % The new rate is based on an increasing block rate structure. % For example in 1991, the first 1200 cubic % feet consumed by residential users were charged at $2.011 per 100 cubic feet, % the next 2800 cubic feet were charged at $2.120 per 100 cubic feet, and the % remainder was charged at $2.228 per 100 cubic feet. % From June 1993 onwards, % the environmental tax was added to the bill of water consumption, this tax % rate charges of $0.254 per 100 cubic feet. % % Original Source: London P.U.C. % % Brief Summary Of The Data Files In The Directory mhsets/londonwq % % 1. CONSUM.1 % Total consumers 01/83 -04/94 % #missing value for June 1988 (66-th obs.) estimated by % #intervention analysis % % 2. PREC.1 % Monthly precipitation (millimeter), 01/83 - 04/94 % % 3. TEMPER.1 % Monthly temperature (celcius), 01/83 - 04/94 % % 4. WATERQ.1 % Residential water consumption, 1983:1-1994:4 % #missing value for June 1988 (66-th obs.) estimated by % #intervention analysis % ---------------------------------------------------------------------------- % % MISC % Miscellaneous time series. % % Brief Summary Of The Data Files In The Directory mhsets/misc % % 1. CAFFEINE.1 % CAFFEINE LEVELS IN INSTANT COFFEE (SEASONAL PERIOD = 5) % % 2. CIGB.2 % Biomonthly cigarette consumption and price, 1966-74 % #consumption per adult in real dollars % #real price index of cigarettes % #Ref: McLeod (1977) Ph.D. Thesis: Topics in Time Series. % % 3. FREEDMAN.1 % Freedman's Nonlinear Time Series % #z_t = f(z_(t-1)), where f(x)=2x if x<=0.5 and f(x)=2-2x, x>0.5 % % 4. KINGS.1 % Age of Death of Successive Kings of England % #starting with William the Conqueror % #Source: McNeill, "Interactive Data Analysis" % % 5. LOGISTIC.1 % logistic map, mu=3.9 % #z_t = mu z_ t-1 (1-z_ t-1 ) % % 6. PACK.2 % Y - INDOOR TEMPERATURE, X - OUTDOOR TEMPERATURE % #original data from a paper by D. Pack % % 7. PAPER.2 % PAPER-MAKING PROCESS DATA (TEE AND WU). OUTPUT AND INPUT VARIABLE % % 8. QBIRTHS.1 % Number of births, daily, Quebec, January 1, 1977 to December 31, 1990. % #source: B. Quenneville, Statistics Canada % % 9. SALESX.1 % SALES OF COMPANY X, JAN. 1965 TO MAY 1971 % #Reference: Chatfield, C. and Prothero, D.L. (1973). % #Box-Jenkins seasonal forecasting: problems in a case-study % #Journal of the Royal Statistical Society A, Vol. 136, pp.295--336 % % 10. SAUGEEN.1 % Mean daily Saugeen riverflows, Jan 1, 1915 to Dec 31, 1979 % % 11. SIMAR4.1 % Simulated AR(4), beta=(2.7607, -3.8106, 2.6535, -0.9238), n=800 % #bimodal spectral density, peaks are close together % #see Percival and Walden (1994) % # "Spectral Analysis for Physical Applications", Cambridge Univ. Press % # p.46, equation (46a) % ---------------------------------------------------------------------------- % % MONTHLY % Miscellaneous monthly time series. % % Brief Summary Of The Data Files In The Directory mhsets/monthly % % % 1. AROSA.1 % ozone, arosa, 1932-72, i=23,63,235,275,462 % % 2. AZUSA.1 % Ozone concentration, AZUSA, 1956.1-1970.12 % % 3. BAYDU.1 % Bay du Nord River, monthly flow, 1953-81, missing values at 327,328 % #used as a covariate with the Piper's Hole River dataset % % 4. CO2.1 % Co_2 (ppm) Mauna Loa. 1965.1-1980.12 % % 5. CPI.1 % Monthly CPI, Canada, 1950-73 % % 6. DESCRIBE % Brief Summary Of The Data Files In The Directory c:\hmsets\monthly % % 7. ELBE.1 % ELBE RIVER, MONTHLY RIVERFLOWS, 300 VALUES % % 8. ENGINES.1 % Motor vehicles engines and parts/CPI Canada, 1976.5-1991.12. IV=164 % % 9. FRASER.1 % Fraser River at Hope, 1913.3-1990.12 % % 10. FURNAS.DAT % 006 FURNAS - VAZOES MEDIAS MENSAIS (M3/S) - 1931 A 1978 % % 11. GUELPH.1 % Phosphorous Data,Speed River,Guelph,1972.1-1977.12,IV=26,ms=6,19,25,41 % % 12. HANKOU.1 % Monthly Flows, Chang Jiang at Han Kou, 1865-1979 % % 13. NIAGARA.1 % NIAGARA RIVER AT QUEENSTON - STATION NO. 02HA003, 1860-1990 % #MONTHLY MEAN DISCHARGES IN CUBIC METRES PER SECOND FOR THE PERIOD OF RECORD % #LOCATION - LAT 43:09:25N DRAINAGE AREA 686000 km2 % # LONG 079:02:50W REGULATED SINCE 1955 % % 14. NIGERIA.1 % NIGERIA POWER CONSUMPTION, 123 VALUES % % 15. NILEMON.1 % Mean monthly Nile river flow, cms, at Aswan, 1870.3-1932.12 % % 16. OZONE.1 % Ozone concentration, downtown L.A., 1955.1-1972.12 % % 17. PEAS.1 % PRECIPITATION IN MM., Monthly, EASTPORT, USA, 1887-1950 % % 18. PIPER.1 % Piper's Hole River, mean monthly flow, 1953-81, fire at 104-6 % % 19. PPHIL.1 % MONTHLY PRECIPITATION, MM., PHILADELPHIA, 1820-1950 % % 20. README % Miscellaneous monthly time series. % % 21. REDDEER.1 % MONTHLY RIVERFLOW OF RED DEER RIVER AT RED DEER ALBERTA, 1942-74 % % 22. RIOTIETE.1 % VAZOES MEDIAS MENSAIS DO RIO TIETE - POSTO CUMBICA - 1948 A 1978 % % 23. SALESX.1 % Sales of company x, January 1965 to May 1971 % #from paper of Chatfield and Prothero, JRSS A (1973) % #Box-Jenkins seasonal forecasting: problems in a case study % % 24. SSASK.1 % S. SASK. RIVER AT SASKTOON- 780 MONTHLY FLOWS IN CMS-JAN 1912 TO DEC 1974 % % 25. SUNSPTMO.1 % Zurich Monthly Sunspot Numbers 1749 - 1983 % % 26. TPMON.1 % MONTHLY TEMPERATURES IN ENGLAND (F), 1723-1970, 2976 VALUES % % 27. TSEOIL.1 % Shartes traded in Oil and Mining stock, TSE, iv=320 % #Kuiwait invasion occurred at t=320 % % 28. WOODS.1 % LAKE OF THE WOODS AT WARROAD - STATION NO. 05PD001 % #MONTHLY MEAN WATER LEVELS IN METRES FOR THE PERIOD OF RECORD % #1916-1965 % #LOCATION - LAT 48:54:20N % # LONG 095:19:00W REGULATED % #WATER LEVELS REFERRED TO LAKE OF THE WOODS DATUM % % 29. WQLONDON.1 % London, Ontario, Monthly Water Useage, 1966-1988 (Ml/day) % ---------------------------------------------------------------------------- % % NOAKES % Monthly riverflow time series used in the forecasting experiments reported % in the article "Forecasting monthly riverflow time series" by D.J. Noakes, % A.I. McLeod & K.W. Hipel (1985), International Journal of Forecasting, % Vol. 1, pp.179-190. % See also: % A.I. McLeod, D.J. Noakes, K.W. Hipel & R.M. Thompstone (1987). ``Combining % hydrologic forecasts''. Journal of the American Society of Civil Engineers, % Water Resources Planning and Management Division, V.113, pp.29-41. % % Brief Summary Of The Data Files In The Directory mhsets/noakes % % 1. AMERICAN.1 % AMERICAN RIVER AT FAIR OAKS, CALIFORNIA, OCTOBER 1906 - SEPTEMBER 1960 % % 2. BOISE.1 % BOISE RIVER NEAR TWIN SPRINGS, IDAHO,OCTOBER 1912 TO SEPTEMBER 1960 % % 3. CLEARWAT.1 % CLEARWATER RIVER AT KAMIAH, IDAHO 1911 TO 1965 % % 4. COLUM.1 % STATION NO. 08NA002 COLUMBIA RIVER AT NICHOLSON 1933-69 37 YRS. % % 5. CURRENT.1 % CURRENT RIVER AT VAN BUREN, MO 1922 TO 1960 % % 6. ENGLISH.1 % STATION 05QA001 ENGLISH R. NEAR SIOUX LOOKOUT O. 1922-77 % % 7. FEATHER.1 % FEATHER RIVER AT OROVILLE, CALIFORNIA, OCTOBER 1902 - SEPTEMBER 1977 % % 8. JAMES.1 % JAMES RIVER AT BUCHANAN, VA 1911 TO 1960 % % 9. JUDITH.1 % JUDITH RIVER NEAR UTICA, MT. 1920 TO 1960 % % 10. MAD.1 % MAD RIVER NEAR SPRINGFIELD, OH. 1915 TO 1960 % % 11. MADISON.1 % MADISON RIVER NEAR WEST YELLOWSTONE, MT. 1923 TO 1960 % % 12. MBOULDER.1 % MIDDLE BOULDER CREEK AT NEDERLAND, CO. 1912 TO 1960 % % 13. MCKENZIE.1 % MCKENZIE RIVER AT MCKENZIE BRIDGE, OREGON, OCTOBER 1911 TO SEPTEMBER 1960 % % 14. MISINAB.1 % STATION NO. 04LJ001 MISSINAIBI RIVER AT MATTICE 1921-76 56 YRS. % % 15. NAMAKAN.1 % STATION 05PA006 NAMAKAN R. AT LAC LA CROIX ONT. 1923-77 % % 16. NECHES.1 % NECHES RIVER NEAR ROCKLAND, TEXAS 1914 TO 1960 % % 17. NMAGNET.1 % STATION 02EA005 N. MAGNETAWAN R., BURKS FALLS O. 1916-77 % % 18. OOSTANAU.1 % OOSTANAULA RIVER AT RESACA, GA 1893 TO 1960 % % 19. PIGEON.1 % STATION 02AA001 PIGEON R. NEAR MIDDLE FALLS ONT. 1924-77 % % 20. RAPPAHAN.1 % RAPPAHANNOCK RIVER NEAR FREDERICKSBURG, VA 1911 TO 1960 % % 21. RICHELU.1 % STATION 02OJ007 RICHELIEU R. AT FRYERS RAPDS QUE 1938-77 % % 22. RIOGRAND.1 % 006 FURNAS - VAZOES MEDIAS MENSAIS (M3/S) - 1931 A 1978 % % 23. SAUGEEN.1 % SAUGEEN RIVER, WALKERTON, 1915-1976 % % 24. SFSKYKOM.1 % S.F. SKYKOMISH RIVER NEAR INDEX, WASHINGTON,OCTOBER 1923 TO SEPTEMBER 1960 % % 25. SSASK.1 % S. SASK. RIVER AT SASKTOON- 624 MONTHLY FLOWS IN CMS-OCT 1911 TO OCT 1963 % % 26. STJOHNS.1 % STATION 01AD002 SAINT JOHNS R. AT FORT KENT N.B. 1927-77 % % 27. TRINITY.1 % TRINITY RIVER AT LEWISTON, CALIFORNIA, OCTOBER 1912 - SEPTEMBER 1960 % % 28. TURTLE.1 % STATION 05PB014 TURTLE R. NEAR MINE CENTRE ONT. 1921-77 % % 29. WBDELAWA.1 % WEST BRANCH DELAWARE RIVER AT HALE EDDY, NY 1916 TO 1960 % % 30. WOLF.1 % WOLF RIVER AT NEW LONDON, WI 1914 TO 1960 % ---------------------------------------------------------------------------- % % PROTHERO % Contains quarterly U.K. economic time series from a case study reported % by D.L. Prothero and K.F. Wallis (1976), "Modelling macroeconomic time % series (with discussion)", Journal of the Royal Statistical Society, A, % Vol.139, Part 4, pp.468-500. % % Prothero and Wallis fitted several models to each series and compared % their performance with a multivariate model. % % Acknowledgment: I would like to thank D.L. Prothero for sending % this data to me. % % Brief Summary Of The Data Files In The Directory mhsets/prothero % % 1. CD.1 % CD(1), CONSUMER EXPENDITURE ON DURABLE GOODS, QUARTERLY % % 2. CN.1 % CN(2), CONSUMER EXPENDITURE ON ALL OTHER GOODS AND SERVICES, QUARTERLY % % 3. I.1 % I(3), INVESTMENT, QUARTERLY % % 4. IV.1 % IV(4), INVENTORY INVESTMENT, QUARTERLY % % 5. M.1 % M(5), IMPORTS OF GOODS AND SERVICES, QUARTERLY % % 6. Y.1 % Y(7), GROSS DOMESTIC PRODUCT, QUARTERLY % % 7. YD.1 % YD(6), PERSONAL DISPOSABLE INCOME, QUARTERLY % ---------------------------------------------------------------------------- % % PRUSCHA % Temperature time series data for Munich-Riem, 1981-1984 from % "A note on time series analysis of yearly temperature data", % Journal of the Royal Statistical Society, A, Vol. 149, Part 2, % pp. 174--185 by Helmut Pruscha (1984). % Acknowledgment: I would like to thank Professor Pruscha for sending % this data to me via e-mail. % Brief Summary Of The Data Files In The Directory mhsets/pruscha % % 1. SUMMER.1 % Mean summer temperature (153 days) Deg C., 1781-1988,, Munich-Riem % % 2. WINTER.1 % Winter negative temperature sum, deg. C., 1781-1988, Munich-Riem % % 3. YEAR.1 % Mean annual temperature, Deg C., 1781-1988,, Munich-Riem % ---------------------------------------------------------------------------- % % ROBERTS % Selected interesting time series from Appendix A of H. Roberts (1992) % "Data Analysis for Managers" published by Scientific Press. % % Brief Summary Of The Data Files In The Directory mhsets/roberts % % 1. AARIVINT.1 % Intervals between aircraft arrivals in control zone % % 2. ALIGN.1 % The total number of alignment errors per airplane in a sample of 50 planes. % #Original Source: Grant and Leavenworth. % % 3. ATT.1 % Returns for AT&T, 1961:1-1967:12 % #84 MONTHS DATA--JAN 1961 THRU DEC 1967--ON RETURNS FOR AT&T % #see also NYSE.1, IBM.1 % % 4. BEARDS.1 % Percent of Men with full beards, 1866-1911, annual % #see also, skirts.1 % #SEE MARIJA NORUSIS'S 1981 SPSS PRIMER FOR DETAILS AND % #ADDITIONAL DATA EXTENDING BACK TO 1842 AND FORWARD TO 1953 % % 5. BLUME.1 % Monthly unit sales, Winnebago Industries, Inc., Nov. 1966 - Feb. 1972. % % 6. BOXHU1.1 % #Yields of 20 consecutive batches of a chemical process. % #The first 10 batches were run under a standard process and the % #second 10 under a modified process aimed at increasing mean % #yield. Source: Box, Hunter, and Hunter, Statistics for % #Experimenters, Wiley, 1978. % % 7. BOXHUN.1 % Production record of 210 consecutive yield values. % #Taken from Box, Hunter, and Hunter, *Statistics for Experimenters*, % #Wiley, 1978, pages 32-3. % % 8. CCPI.1 % One-month change in CPI, 1963:4-1971:7 % #see also, tbills.1, scoles.1 % % 9. CRYER.1 % Chemical process data % #from "The Estimation of Sigma for an X Chart: MR/d2 or % #S/c4", Jonathan D. Cryer and Thompas P. Ryan, manuscript, February, 1989 % % 10. DJ.1 % Monthly closings of the Dow-Jones Industrial Index Aug 1968 - Aug 1981 % % 11. DJWEEK.1 % WEEKLY CLOSINGS OF THE DOW-JONES INDUSTRIAL AVERAGE, July 1971-Aug 2, 1974 % #JULY 1971 THROUGH 2 AUGUST 1974. DATA QUOTED IN UNPUBLISHED PAPER BY D. % #A. HSU, TAKEN FROM "NEW YORK STOCK EXCHANGE: STOCK PRICES", PUBLISHED % #QUARTERLY BY STANDARD AND POOR CO., NEW YORK, N.Y. % % 12. EGDEMAN.2 % Measurements of center thickness and axial difference % #Measurements of center thickness (in mils) and axial difference (in mils) of % #25 contact lenses pulled from the production process at regular intervals. % #Tolerances: 0.4 mil +/- 0.01 mil for center thickness; axial difference must % #be less than 0.0025 mil. % #Taken from Rick L. Edgeman and Susan B. Athey, "Digidot Plots for Process % #Surveillance", Quality Progress, May, 1990, 66-68. % % 13. G.1 % NOMINAL GOVERNMENT PRODUCT (BILLION DOLLARS) 1929-1974, U.S. % % 14. GLOBWARM.1 % Surface air "temperature change" for the globe, 1880-1985. Degrees Celsius. % #"Temperature change" actually means temperature against an arbitrary zero % #point. From James Hansen and Sergej Lebedeff, "Global Trends of Measured % #Surface Air Temperature", `Journal of Geophysical Research`, Vol. 92, No. % #D11, pages 13,345-13,372, November 20, 1987. % % 15. GNPN.1 % NOMINAL GNP (BILLION DOLLARS) 1890-1974, U.S. % % 16. GNPR.1 % REAL GNP (BILLION DOLLARS) 1890-1974, U.S. % % 17. GRANT.1 % Diameters, consecutive batches of 5 % #100 measurements of pitch diameter -- DIAM -- of threads on % #aircraft fittings. Values expressed in units of 0.0001 inch in % #excess of 0.4000 inch. Specifications call for "37 plus or minus % #13". Each successive group of five readings are items % #consecutively produced at times about one hour apart. From Eugene % #L. Grant, Statistical Quality Control, McGraw-Hill, 1946. % % 18. GRUEN.1 % Quarterly unit sales of the SPSS Manual, 1976:1-1982:4 % #Quarterly unit sales of the SPSS Manual, Second Edition, from % #1976:1 through 1982:4. (SPSS is a leading statistical computing % #package; the manual was actually sold through McGraw-Hill, Inc.) % % 19. HALSEY.1 % Degree days per heating in Chicago, 1931:2 - 1977:8, monthly % #DEGREE DAYS PER HEATING YEAR IN CHICAGO, 1931-2 TO 1977-8. % #A DEGREE DAY IS THE DIFFERENCE BETWEEN 65 DEGREES F. AND THE ACTUAL % #DAILY MEAN TEMPERATURE IF THE LATTER IS 65 DEGREES OR LESS; % #OTHERWISE THE VALUE IS ZERO. THE SUM OF DEGREE DAYS FROM JULY 1 % #THROUGH THE FOLLOWING JUNE 30 -- DDAYS -- IS A MEASURE OF COLD WEATHER % #SEVERITY. % % 20. HARBOR.1 % Mean July water level, Harbor Beach, Michigan, 1860-1986 % #Mean July average water surface elevation, in feet, IGLD (1955) % #for Harbor Beach, Michigan, on Lake Huron, Station 5014. 1860--1986. % #Source: Great Lakes Water Levels, 1860-1986. U.S. Dept. of Commerce, % #National Oceanic and Atmospheric Administration, National Ocean Survey. % % 21. IBM.1 % Monthly returns, IBM common stock. Jan. 1961-Dec. 1967. % #see also NYSE.1, ATT.1 % % 22. IPI.1 % IMPLICIT PRICE INDEX 1890-1974, U.S. % % 23. IRONSU.3 % 39 daily observations, blast furnace data (bof, sulfur, coke) % #39 DAILY OBSERVATIONS OF: % #BOF--SULFUR IN BASIC OXYGEN STEEL % #SULFUR--SULFUR IN HOT METAL % #COKE--MOISTURE IN COKE USED % #FOR A BLAST FURNACE OPERATION % # BOF SULFUR COKE % % 24. ISH66.1 % Quality control data, 5 measurements per day % #Data from Ishikawa, *Guide to Quality Control*, Table 7.2, page 66. % #Each row shows five measurements taken at successive times on a given day: % #6:00, 10:00, 14:00, 18:00, and 22:00. Thus the 25 rows represent 25 days, % #which we shall assume to be consecutive working days. % % 25. JOE.3 % #Three monthly series for the period 1954:1 to 1985:12. % #The first series is the commercial paper rate, expressed by the annual % #percentage rate, e.g. 8.36. % #The second series is the monthly return on the S&P 500 index. % #The third series is the return, before transaction costs, to an % #investment strategy based on the commercial paper rate. % % 26. LAKEMICH.1 % Highest mean monthly level, Lake Michigan, 1860-1955 % #Lake Michigan-Huron, highest monthly mean level for each calendar year, % #1860-1955. (Add 500 to get height in feet above sea level.) % % 27. LYNDPIN.2 % Annual Domestic Sales and Adverstising, Pinkham Medicine, 1907-60 % #Annual domestic sales and advertising of Lydia E. Pinkham Medicine % #Company, 1907-1960 (in $1000). Source: Kristian S. Palda, The % #Measurement of Cumulative Advertising Effects, Prentice-Hall, % #Englewood Cliffs, N.J., 1964, page 23. % #AD: advertising % #SA: sales % % 28. M.1 % MONEY SUPPLY (BILLION DOLLARS) 1890-1974, U.S. % % 29. NYSE.1 % Monthly returns, NYSE. Jan. 1961-Dec. 1967. % #see also ATT.1, IBM.1 % % 30. PGREATL.1 % Annual precipitation, inches, Great Lakes, 1900-1986 % #Source: Great Lake Water Levels, U.S. Dept of Commerce, Rockville MD % # U.S. Lake Survey, Detroit, MI, US Army Corps of Engineers % % 31. PLHURON.1 % Annual precipitation, inches, Lake Huron, 1900-1986 % #Source: Great Lake Water Levels, U.S. Dept of Commerce, Rockville MD % # U.S. Lake Survey, Detroit, MI, US Army Corps of Engineers % % 32. PLMICH.1 % Annual precipitation, inches, Lake Michigan, 1900-1986 % #Source: Great Lake Water Levels, U.S. Dept of Commerce, Rockville MD % # U.S. Lake Survey, Detroit, MI, US Army Corps of Engineers % % 33. PLSUPER.1 % Annual precipitation, inches, Lake Superior, 1900-1986 % #Source: Great Lake Water Levels, U.S. Dept of Commerce, Rockville MD % # U.S. Lake Survey, Detroit, MI, US Army Corps of Engineers % % 34. RGNP.1 % REAL GNP IN BILLIONS OF DOLLARS, USA, 1890-1974 % % 35. ROCKY.1 % Rockwell hardness, 100 coils produced in sequence at a Chicago Steel Mill % #ROCKWELL HARDNESS (MEASURED ON ROCKWELL "B" SCALE) OF A SAMPLE OF 100 STEEL % #COILS PRODUCED IN SEQUENCE IN A CHICAGO STEEL MILL. % % 36. SCHOLES.1 % Scholes Index for NYSE, 1963:4-1971:7 % #RETV: SCHOLES INDEX FOR NYSE: VALUE-WEIGHTED RETURNS WITH REINVESTMENT OF % # DIVIDENDS % #see also, tbills.1, ccpi.1 % % 37. SKIRTS.1 % Diameter of skirts at hem, 1866-1911, annual % #see also beards.1 % #SEE MARIJA NORUSIS'S 1981 SPSS PRIMER FOR DETAILS AND % #ADDITIONAL DATA EXTENDING BACK TO 1842 AND FORWARD TO 1953 % % 38. SNOW.1 % Chicago Snowfall, 1939-78 % #CHICAGO SNOWFALL DATA FOR 40 YEARS, TOTAL IN INCHES, STARTING WITH 1939 AND % #ENDING WITH 1978. % % 39. TBILLS.1 % One-month return on U.S. Treasury Bills, 1963:4-1971:7 % #see also, ccpi.1, scoles.1 % % 40. U.1 % Civilian unemployment rate 1890-1974, U.S. % % 41. VELMON.1 % Velocity of money, U.S. economy, 1869-1960, annual % #FRIEDMAN AND SCHWARTZ DATA ON VELOCITY OF MONEY FOR THE AMERICAN % #ECONOMY FROM 1869 TO 1960. % % 42. YULE1.1 % Standardized mortality per 1000 persons, England, 1866-1911 % #see also yule2.1 % #ANNUAL DATA FOR 1866-1911 % #MORTAL: STANDARDIZED MORTALITY PER 1000 PERSONS IN ENGLAND AND WALES % #MARRAG: PROPORTION OF CHURCH OF ENGLAND MARRIAGES PER 1000 OF % # ALL MARRIAGES % #SOURCE: G. UDNY YULE, "WHY DO WE SOMETIMES GET NONSENSE-CORRELATIONS % #BETWEEN TIME-SERIES?", JOURNAL OF THE ROYAL STATISTICAL SOCIETY, 89, % #JANUARY, 1926, 1-69. NUMBERS READ FROM GRAPH ON PAGE 3. YULE'S % #CORRELATION FROM ORIGINAL DATA IS 0.9512. CORRELATION COMPUTED FROM % #NUMBERS IS 0.9515. % #MORTAL % % 43. YULE2.1 % Proportion of Church of England Marriages/1000 persons, England, 1866-1911 % #see also yule2.1 % #ANNUAL DATA FOR 1866-1911 % #MORTAL: STANDARDIZED MORTALITY PER 1000 PERSONS IN ENGLAND AND WALES % #MARRAG: PROPORTION OF CHURCH OF ENGLAND MARRIAGES PER 1000 OF % # ALL MARRIAGES % #SOURCE: G. UDNY YULE, "WHY DO WE SOMETIMES GET NONSENSE-CORRELATIONS % #BETWEEN TIME-SERIES?", JOURNAL OF THE ROYAL STATISTICAL SOCIETY, 89, % #JANUARY, 1926, 1-69. NUMBERS READ FROM GRAPH ON PAGE 3. YULE'S % #CORRELATION FROM ORIGINAL DATA IS 0.9512. CORRELATION COMPUTED FROM % #NUMBERS IS 0.9515. % # MARRAG % ---------------------------------------------------------------------------- % % SANFRAN % A case study with monthly riverflow, precipitation and temperature. % % Brief Summary Of The Data Files In The Directory mhsets/sanfran % % 1. FLOW.1 % SAN FRANCISCO RIVER, GLENWOOD, CMS, MONTHLY, 1928-1966 % % 2. PRECIP.1 % MONTHLY PRECIPITATION, MM, SOUTHWESTERN MOUNTAIN REGION, 1932-1966 % % 3. TEMPER.1 % MONTHLY MEAN TEMPERATURES, SOUTHWESTERN MOUNTAIN REGION, F., 1932-1966 % ---------------------------------------------------------------------------- % % % THOMPSTO % Quarter-monthly (i.e., s=48) hydrological time series used in the article % "Forecasting quarter-monthly riverflow" by R.M. Thompstone, K.W. Hipel and % A.I. McLeod (1985), Water Resources Bulletin, Vol.21 No.5, pp.731-741 % See also: % A.I. McLeod, D.J. Noakes, K.W. Hipel & R.M. Thompstone (1987). ``Combining % hydrologic forecasts''. Journal of the American Society of Civil Engineers, % Water Resources Planning and Management Division, V.113, pp.29-41. % % Brief Summary Of The Data Files In The Directory mhsets/thompsto % % 1. LACSTJIN.1 % Lac St-Jean Reservoir, quarter-monthly inflows, 1953-82 % % 2. LACSTJRA.1 % Lac St-Jean Region, quarter-monthly rainfall, 1953-82 % % 3. LACSTJSN.1 % Fonte de neige par quart de mois, 1953-82, Bassin Daval % ---------------------------------------------------------------------------- % % WISCONSI % Wisconsin employment time series. % Contains time series of employment, in units of 1000 employees, % of various industries in Wisconsin. % % Miller and Wichern (1977) fit seasonal ARIMA models to these time % series data in their book. McLeod (1993) pointed out that some % of these time series exhibit periodic correlation. The data are % listed in Miller and Wichern's book. % % REFERENCES: % Miller, R.B. & Wichern, D.B. (1977). "Intermediate Business Statistics" % San Francisco: Holden-Day. % % McLeod, A.I. (1993). "Parsimony, Model Adequacy and Periodic Correlation % in Time Series Forecasting", International Statistical Review, % Vol. 61, pp.387--393. % % Brief Summary Of The Data Files In The Directory mhsets/wisconsi % % 1. FOOD.1 % Food and Kindred Products, Jan 1961-Oct 1975 % % 2. METALS.1 % Fabricated Metals % % 3. TRADE.1 % Trade, Jan 1961-Oct 1975 % % 4. TRANEQ.1 % Transportation Equipment, Jan 1961-Oct 1975 % ---------------------------------------------------------------------------- % % % % % % % File: ../data/mhsets/MONTHLY/HANKOU.1 % % File specific information: % Monthly Flows, Chang Jiang at Han Kou, 1865-1979 % % % Information about the dataset % CLASSTYPE: numeric % CLASSINDEX: last % @relation mhsets-HANKOU @attribute value INTEGER @data 3880 3290 4910 8760 13800 21700 32400 41400 39600 34600 23300 8720 4170 5750 10700 17500 29400 37300 45700 51800 46700 32300 18200 8140 5540 7750 11100 16900 24800 31000 39000 44500 45700 30100 20500 13100 7990 6630 13500 19800 25600 27800 34200 41200 44400 16900 39700 24600 13800 12600 20000 22600 27000 36100 48400 50200 50000 41500 28400 13500 7470 5490 7080 13100 21600 33900 50300 58100 42100 30700 18500 9490 6120 6230 9770 9960 19200 23700 37100 42000 44400 39700 33000 16100 8000 8310 13200 16700 26300 40400 49000 41300 34600 29500 19000 9110 6420 5310 6430 11400 12900 23100 39300 43200 40800 35500 26100 12200 6890 10100 18900 19900 23200 21500 32000 33400 32400 36000 28100 13700 7310 7480 16600 18200 26600 31700 42600 40500 36300 28800 15600 9620 5800 9550 15500 17700 28100 36800 46300 44300 37700 28500 18500 9500 5420 9080 7870 16700 28500 28000 27500 28600 28100 27000 14400 9960 6640 7380 13700 22400 21800 26700 46600 51500 44000 35400 32100 14800 7240 6510 9570 9460 19000 31800 40700 36100 29500 24400 16300 7780 5590 9420 12200 13900 16300 27800 37800 36000 36300 25700 13400 7100 5120 5690 9380 13600 30000 33300 35800 31600 31100 35000 27200 16300 9360 14900 12400 15800 23400 31400 46600 43900 38200 39900 35100 18900 8250 6820 11000 15200 30800 37000 46700 44500 40700 40000 34900 22300 10600 12400 15800 19800 22000 23500 34400 29100 28600 20200 17900 7880 5850 7620 13100 20300 27100 39900 47800 46600 38800 28900 19200 11600 7610 6030 11900 23500 22800 30900 37700 41500 38200 36000 29800 12900 7500 10300 16100 10800 20700 36600 51600 47600 39400 34200 20900 7930 5370 7840 11700 21300 31400 30100 38400 41000 36900 26000 14400 9350 6460 6760 5800 14100 26600 32500 43000 47500 48800 51400 37700 18200 9390 8710 13000 19900 29600 38300 47000 50400 48500 36700 17200 11300 7500 6130 10800 13500 17400 24600 40400 41800 35700 32500 30900 11900 6650 7000 7250 14200 30000 33300 42800 41700 35000 27700 22300 14100 6890 7580 12800 15200 18800 29800 39500 46000 42400 35600 19700 8960 6160 6740 16500 14400 27400 41000 39200 33600 31000 37000 26200 11500 6730 5240 6140 12300 18500 23900 29100 39800 34400 27400 21100 9730 5410 5180 7810 14400 23200 27000 37600 33000 41300 46900 32300 16300 8830 8050 13400 22800 32400 40700 43300 48800 43500 38400 29200 14900 8530 7570 8090 11800 24500 32400 33800 37100 39400 33500 16400 8520 5990 5590 10900 15400 14700 29600 36300 31300 39200 37500 23600 10000 7400 7670 11100 13100 17900 17700 27200 24100 19300 12200 8370 5710 5670 6770 4600 10100 17600 23600 47400 42200 33700 28300 16300 7870 5310 6100 5250 8940 19200 19900 31900 37100 34800 28900 16800 7850 5820 5500 12500 18400 28400 29800 39700 42600 41700 33500 20000 9050 5640 5200 10200 17200 28000 24900 32200 35900 36300 33600 25400 10700 8230 7960 12700 20900 24100 31500 34200 36600 44400 42500 31900 15800 14700 12400 13500 20900 34800 36000 42200 45400 42000 34700 17400 8740 5960 8300 9160 14600 21500 21000 35900 37500 37500 43700 39100 20900 9450 11600 11300 20900 24800 22200 42900 32200 28800 26600 29200 15800 8770 8250 8330 11200 22000 30100 47700 47000 39000 37700 31900 13600 10200 8200 9570 18300 28500 29400 36900 37600 37200 34000 28000 14100 8490 9960 16900 20000 25100 36600 46100 47800 44500 36900 33200 24000 15200 12000 20100 18900 24900 29300 47700 42500 33300 19800 12500 8340 7640 7380 14500 17100 28000 35600 40100 40400 35200 29300 18300 9470 6730 9120 10200 13900 22800 32700 23900 33300 30700 23300 24700 14100 6960 5120 6150 15100 23100 23600 37200 39100 39500 35100 27200 13200 7270 8050 12300 14600 28600 26000 36300 35400 29000 27900 24700 10300 6460 5320 10700 15400 21100 31900 42600 46800 39500 32700 23700 10100 6150 5020 7000 16100 24600 37000 38100 44500 47700 39400 24000 14600 10600 9550 15000 14800 18500 24100 40200 44200 34700 30900 16400 8800 5980 6270 13600 19700 23500 32400 44400 43900 44000 43100 26900 15900 10300 9610 8650 12200 29200 37100 45200 48800 46800 42700 27000 12100 8410 8680 9920 15500 19000 29100 39300 48600 46700 29700 17000 9010 5990 5880 7930 13200 22200 33400 48700 45000 36800 26600 17700 11100 7340 10200 9780 15100 32700 28900 56200 51700 39800 29500 15800 8530 6860 8590 11700 14500 25800 24200 26100 28500 34000 29800 21900 11000 7170 7820 13600 12100 20000 33400 51200 53400 41700 33700 23000 14400 10100 8860 12200 21700 27700 29800 43500 39800 31900 27900 14500 8920 6500 5630 7470 8230 16700 22300 25100 33400 24400 21800 12900 6880 5130 5100 5360 6300 15500 23900 36200 40100 29600 27600 15700 8600 7270 9270 11900 20000 31900 33500 38500 30300 38100 31700 22200 12900 7460 7520 12700 14400 30800 36500 44900 56500 52300 40500 23200 12800 8510 10300 11600 11400 24900 33600 44000 36100 39400 36000 20700 10000 7800 8330 9450 12600 23900 43900 48100 35100 22300 29600 20100 11400 7320 5500 9580 14500 26200 30600 37700 37000 36800 32000 20900 11200 8200 9960 14800 19600 20800 34400 54400 45600 41500 36600 32300 21300 10900 10300 10600 19900 31500 31600 26400 36700 34100 16700 9120 7000 5410 7470 10900 12000 22200 35000 38600 49500 53000 47700 32000 16000 9470 9970 12600 15200 19500 41200 48200 46300 46800 45600 29100 14000 8340 10800 18400 19500 20000 25700 36700 44100 31000 23900 13800 9400 5570 5870 16000 15400 17500 16200 28800 33200 34900 30200 20100 9260 6590 6570 9720 11300 19800 13000 23700 35700 38400 25200 16200 12000 8500 5790 8770 13900 23200 31100 42000 32900 21800 19500 13700 7470 5210 5700 9360 16300 23800 31100 43500 40500 41900 32200 25300 11000 7490 13200 9660 17200 23200 28900 38386 36717 32100 27268 18392 10577 7060 5270 8200 10400 23400 32000 44100 40300 33700 28100 17800 10600 7620 8670 7310 11700 21500 28300 39700 45300 41600 28100 16500 9080 6790 8600 14600 20500 34000 38100 51700 50800 43300 36300 24600 14600 12700 10500 14600 19200 28300 42400 50700 48900 44500 41400 28900 16900 12800 13800 10800 18900 25800 35400 44400 40100 38400 35800 23400 11800 7750 6570 9370 18800 30000 21100 32500 37000 34800 29200 16700 12400 7730 7800 14700 14500 31500 32000 36200 40600 56100 40100 23700 13000 7700 9900 15700 18900 20600 25200 35700 35100 28400 24500 23600 14100 13200 11100 10900 21200 33400 43800 57000 66500 50900 39200 23200 13400 8820 8440 9110 13600 18300 28900 45100 45100 38000 26100 18900 9600 6520 6680 8920 16500 28900 38200 41600 33500 38200 18500 11500 7540 6750 8420 9750 15200 28400 28400 41300 42200 20200 21300 13500 11700 7250 7100 7260 13300 33000 21700 42600 41400 37800 25300 15400 8830 6310 11100 14500 19500 23700 34100 32800 29900 16200 13800 13100 9570 7030 5640 11100 12900 19400 23300 38900 36700 30500 21200 14300 9310 5970 6570 15900 20600 23100 27600 39800 32000 30500 25300 25200 14600 9230 6750 8780 14200 25400 34300 47200 41100 37400 26200 18300 11400 6940 5320 6280 11800 30500 27100 32900 36200 36900 29500 18800 13400 9510 8950 14300 25400 33600 31600 45600 36900 47000 45700 24400 10600 7450 6440 7010 14300 26400 28400 44600 38600 39700 35300 20300 12800 8880 8320 7260 14500 16000 25000 38000 32900 36500 24300 15300 8300 6180 6870 11100 17500 34500 34500 44300 31400 29700 26400 17100 13900 7330 6890 12100 23600 25700 24800 53000 41900 45400 35000 17900 10400 9080 7850 7410 11500 21200 18500 48300 38900 38000 24700 20300 9410 6370 6910 9870 20100 36800 32600 41500 40400 29000 33200 15700 12900 8740 8670 9540 14200 21000 39400 30600 26200 27800 26500 16700 7660 6040 6580 9430 15700 26400 26200 29900 21300 19300 23500 20100 10300 9910 9850 10100 20600 32300 37700 43400 31900 39000 32900 15000 9260 6590 8940 7740 12600 24200 22900 45600 41500 40200 34500 14000 9940 8230 8180 10400 16300 38000 36300 35700 34300 27500 33000 21400 12900 7870 7430 10300 16500 26800 32700 45300 25700 26100 24500 19500 9750 7170 7550 8680 23800 34500 37700 41000 33500 25500 21400 19100 9340 8060 6580 6480 10200 20300 36600 33800 29000 24000 16900 15200 9540 6020 6180 6720 8270 18300 25700 36200 34400 43800 28000 12600 7730