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% 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/ASKEW/ASKEW26.1 % % File specific information: % OOSTANAULA RIVER AT RESACA, GA 1893 TO 1960 % % % Information about the dataset % CLASSTYPE: numeric % CLASSINDEX: last % @relation mhsets-ASKEW26 @attribute value REAL @data 28.3169 43.8911 39.6436 50.2341 170.4108 100.4682 64.5058 93.1058 88.5185 32.9891 27.2125 29.5628 16.3671 16.1123 23.9561 59.3238 104.0927 87.7822 55.1895 40.6630 21.7190 21.6624 23.3331 15.6875 9.5994 13.1673 64.2509 185.6453 92.2280 173.2425 102.1389 88.7450 53.1507 58.8707 55.6143 27.6372 19.5103 27.4390 36.7553 67.9321 119.6670 69.7161 71.4151 46.7794 59.5503 58.4177 18.8024 16.0557 17.7263 51.4800 42.4470 56.2373 132.1264 272.4647 156.2241 63.2315 34.2634 54.3117 27.6372 13.6770 14.3850 15.9141 59.8335 109.5013 43.1549 66.6295 123.6597 37.9446 32.1396 34.7165 59.0406 122.3005 136.7704 68.4701 64.9022 86.7911 275.4097 277.0804 142.9718 60.9945 43.0416 84.2143 37.4066 30.9503 18.0378 21.5491 51.9614 86.9894 146.5680 151.1837 121.7908 50.6022 146.1716 82.2888 39.1905 43.7779 32.6776 58.8707 83.9595 167.2393 123.0367 151.4951 177.2068 146.2848 87.6407 47.1192 161.7175 74.7565 41.8240 33.4705 167.8057 118.5910 150.4757 204.1362 95.9092 50.0642 34.8864 26.3064 22.6252 26.3913 20.9828 27.3258 71.5284 68.3852 225.6853 250.4625 151.5518 56.6054 91.5201 56.2939 47.4874 16.5370 16.5087 21.4359 18.0662 38.6808 61.3626 100.6098 52.0464 30.3273 28.8832 20.1616 31.0636 10.5056 7.3624 9.3729 46.5529 79.0040 195.0465 77.0218 59.0406 97.0135 43.5513 49.7527 48.2802 22.6535 25.4568 20.7279 144.0195 148.8617 60.5131 172.4213 95.4561 62.4103 102.2521 115.5611 88.4335 88.2919 145.8035 170.1276 97.0985 80.7597 132.4096 107.5474 74.3884 89.5379 83.9878 50.1775 32.2529 50.5173 32.1113 75.3511 86.8761 104.9422 169.8162 119.2989 107.0943 75.4644 41.7957 37.4915 35.9341 20.1050 18.5475 15.5743 94.2668 104.3193 209.1483 268.1323 111.8516 142.9718 180.6332 73.9353 67.4507 33.8670 27.6372 15.9141 46.8927 53.8020 74.6432 63.8545 50.5173 150.8155 112.1630 123.1500 60.3149 52.7260 32.6493 26.0515 55.7559 108.4535 105.6502 64.8173 152.1181 54.5949 34.9147 36.4155 23.0499 13.0824 30.7521 39.8418 77.7014 91.9731 156.8753 205.0140 162.1706 105.8484 84.0444 74.7282 58.0495 33.4988 29.1947 24.7206 49.0731 125.7268 143.9629 252.7562 80.0234 71.4717 69.5462 38.9074 23.6163 19.4537 16.7636 15.0079 29.3929 33.4139 66.5446 45.4202 96.8719 35.6792 19.9634 37.2933 28.1469 14.6398 27.7505 15.2345 135.0714 128.1054 157.8098 82.8268 50.9986 62.4387 44.0327 46.7511 33.4988 29.6194 64.7890 40.0400 132.9476 128.8417 128.9266 91.5484 49.3280 43.5796 53.8303 223.4766 57.4266 26.6462 26.6178 30.0725 63.0050 143.7363 184.1445 370.1012 129.0116 58.8141 62.0705 55.9824 53.0375 39.2188 27.4673 18.9157 17.6980 126.2365 142.1223 35.9058 100.9779 62.9200 41.9939 31.5733 27.9204 22.8234 42.7868 67.6773 162.9352 164.4926 168.7118 189.3831 96.1640 80.0801 55.9824 69.0648 50.1208 29.5911 41.7390 33.4422 112.9842 128.3320 184.4560 178.5661 280.1669 115.7026 58.9557 102.9318 195.1031 89.1698 39.1622 48.5068 197.7082 130.0876 287.9824 82.4304 116.2124 62.8068 40.2099 51.7066 52.1313 27.9487 29.7610 82.0622 81.2127 220.0502 159.5938 257.9382 142.0940 118.7609 81.0428 43.8062 28.5434 21.6907 20.8129 17.0751 89.1981 90.3308 138.7242 129.2947 130.5407 187.1461 102.7902 90.2741 61.8157 31.2618 19.7652 24.6357 81.5808 152.8544 106.9244 141.3294 173.2425 107.4908 72.5478 85.9983 29.0531 23.2481 17.1883 15.6309 58.8141 178.0847 70.2258 78.5226 58.7291 35.5660 17.9529 15.9141 8.2685 7.2774 35.7359 56.8602 69.3480 122.2438 87.3858 100.4116 86.7911 39.1905 34.7165 39.4454 75.0680 24.1826 20.5297 49.5545 164.3510 68.3002 122.6969 141.9807 161.5476 57.7664 63.0899 73.1707 42.7301 22.7101 20.1616 36.0473 122.6969 83.3082 75.4927 117.9680 170.1276 99.0807 112.5878 111.5118 63.9111 113.9187 40.9462 41.1727 35.5376 95.9092 116.8353 278.6378 125.5286 238.4562 84.8090 51.3101 55.5293 57.7097 35.3111 260.7132 95.7676 89.5662 103.0733 140.2534 84.3842 62.1838 33.7537 23.8428 17.1600 23.6446 20.0483 56.0957 47.2325 66.2048 65.5535 71.1319 147.8989 64.7890 25.4002 26.9010 26.1081 17.5281 11.2135 13.1957 159.4522 152.2597 230.4142 97.1551 109.0199 111.6817 60.2299 89.3397 38.4543 29.9309 63.1183 128.5868 369.8181 173.8371 179.0191 115.8442 100.0151 103.3565 38.5675 36.6137 34.1501 31.3468 15.5743 17.1317 20.1333 63.6846 58.4743 203.9096 53.8586 38.0578 48.0820 39.8135 52.8676 20.4164 68.0737 27.8071 35.8208 103.9795 90.1892 150.0227 160.9813 78.2961 33.0174 25.6267 24.6923 11.0719 10.5339 51.5084 34.0085 279.0626 225.9118 139.1490 291.9467 52.6410 28.0054 29.7044 32.3095 20.6996 22.4553 18.5759 78.8624 297.3269 142.5753 81.0428 134.4201 128.7567 46.8927 31.1202 44.8256 23.4180 28.6283 20.6713 32.5077 55.9541 46.9777 130.8805 260.7132 56.4921 90.3874 133.8821 58.5026 27.3824 16.7636 36.4155 28.6567 77.8430 245.0257 187.3443 95.2013 68.3852 48.6200 35.5376 38.5675 19.4537 14.0735 12.7426 18.6325 30.8937 92.0581 103.5264 70.8771 36.2456 36.5854 47.6856 32.3378 16.5087 11.9780 17.8396 40.6064 49.8943 29.0814 57.3699 42.1072 20.0200 21.7473 89.7361 28.0337 12.9974 13.7620 21.0961 44.8539 54.5383 143.7080 161.6609 53.6887 44.9672 44.4858 40.0683 85.0921 35.8491 28.0337 25.2303 162.5954 176.3290 129.8611 196.1791 101.9973 54.4533 34.4050 57.4266 36.4721 29.8176 18.4626 21.7757 35.1978 70.9337 237.1536 278.4679 171.3736 79.1739 36.8969 26.9860 24.0127 15.2061 17.2166 16.5937 34.3200 71.4151 193.5174 106.0749 94.7199 90.5290 36.5004 32.5644 38.3127 24.7206 23.0216 37.9729 104.0078 267.2827 304.1230 162.9635 128.0771 173.3841 83.8462 58.8141 26.6462 23.6729 23.7295 50.5173 51.0836 350.8458 86.5363 108.2836 104.2910 55.8975 41.3709 26.9293 19.5103 15.0362 16.4238 31.7432 39.3887 45.8167 251.2837 135.3262 109.3597 39.3321 25.7117 31.2901 41.7390 18.2927 14.6964 159.9053 183.3799 215.2364 202.8053 93.8137 119.7520 84.7806 48.0537 71.3585 42.9567 46.2131 54.5099 85.0072 75.8042 145.6052 150.1926 207.5625 76.5404 52.7543 82.6569 87.6690 43.3531 102.6203 33.0741 29.3363 54.7082 62.8917 106.5846 200.6249 230.3009 52.4711 44.1460 46.6662 26.7028 32.6493 20.0483 61.3626 191.3086 147.7573 109.8411 245.6487 91.2935 54.5949 48.1103 21.1244 30.9786 24.2109 15.6875 22.3703 50.2058 146.6246 197.4817 108.9916 62.2404 111.4834 30.6671 40.0967 18.0662 23.2198 14.8097 15.1778 58.6725 256.4091 67.1676 130.7955 111.1153 61.8157 40.0117 23.3331 24.4941 10.8737 9.7410 13.7903 50.4323 58.2761 161.3777 110.6056 120.7997 75.6909 36.3305 37.3782 22.2854 12.7426 18.1511 30.4689 30.6388 27.1275 262.4972 134.1652 175.2247 82.0905 32.7909 32.1396 19.0856 18.1794 15.5176 17.3299 63.6280 75.8325 272.6063 102.3937 173.4407 51.5367 57.0018 30.7521 16.0273 47.8838 46.8927 169.1365 130.1726 83.8462 124.8490 104.6591 117.3450 142.7169 33.9519 71.3868 34.3483 28.8549 23.1632 23.0499 27.8921 76.7670 87.1876 82.6852 130.0593 61.1078 65.1288 36.2173 21.5208 23.3897 33.8103 68.3569 80.5331 91.2086 134.6466 164.7474 85.1771 45.9866 28.2602 21.1244 33.9802 28.3169