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1

Erhardt, Gregory D., Jawad Hoque, Mei Chen, et al. Traffic Forecasting Accuracy Assessment Research. Transportation Research Board, 2020. http://dx.doi.org/10.17226/25637.

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2

Fund, International Monetary. Forecasting accuracy of crude oil futures prices. International Monetary Fund, 1991.

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3

Fildes, Robert. Accuracy gains through individual univariate forecasting: Model selection. Manchester Business School, 1986.

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4

Makridakis, Spyros. "Metaforecasting: Ways of improving forecasting. Accuracy and Usefulness". INSEAD, 1986.

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5

National Renewable Energy Laboratory (U.S.) and International Workshop on the Integration of Solar Power into Power Systems (3rd : 2013 : London, England), eds. Metrics for evaluating the accuracy of solar power forecasting. National Renewable Energy Laboratory, 2013.

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6

Grissmer, David W. The accuracy of simple enlisted force forecasts. Rand, 1985.

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7

Stephen, MacDonald. The accuracy of USDA's export forecasts. U.S. Dept. of Agriculture, Economic Research Service, Commodity Economics Division, 1992.

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8

Berger, Helge. Forecasting ECB monetary policy: Accuracy is (still) a matter of geography. International Monetary Fund, European Dept., 2006.

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9

Fildes, Robert. The impact of empirical accuracy studies on time series analysis and forecasting. INSEAD, 1993.

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10

National Research Council (U.S.). Committee for a Workshop on Weather Forecasting Accuracy for FAA Air Traffic Control. Weather forecasting accuracy for FAA traffic flow management: A workshop report. National Academies Press, 2003.

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11

Rich, Robert W. Modeling uncertainty: Predictive accuracy as a proxy for predictive confidence. Federal Reserve Bank of New York, 2003.

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12

Ash, J. C. K. The accuracy of OECD forecasts for Canada and the United States. University of Reading. Department of Economics, 1991.

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13

Ash, J. C. K. The accuracy of OECD forecasts for Canada and the United States. University of Reading, Dept. of Economics, 1991.

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14

Moran, Kevin. Estimated DGE models and forecasting accuracy: A preliminary investigation with Canadian data. Bank of Canada, 2002.

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15

Moran, Kevin. Estimated DGE models and forecasting accuracy: A preliminary investigation with Canadian data. Bank of Canada, 2002.

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16

Makridakis, Spyros. Exponential smoothing: The effect of initial values and loss functions on post-sample forecasting accuracy. INSEAD, 1990.

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17

Makridakis, Spyros. Exponential smoothing: The effect of initial values and loss functions on post-sample forecasting accuracy. INSEAD, 1991.

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18

Werner, Arber, Cabibbo N, Sánchez Sorondo Marcelo, and Pontificia Accademia delle scienze, eds. The proceedings of the plenary session on predictability in science: Accuracy and limitations : 3-6 November 2006. Pontifical Academy of Sciences, 2008.

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19

Fortune, Michael A. Automated satellite-based estimates of precipitation: An assessment of accuracy. U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, National Environmental Satellite, Data, and Information Service, 1998.

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20

Fortune, Michael A. Automated satellite-based estimates of precipitation: An assessment of accuracy. U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, National Environmental Satellite, Data, and Information Service, 1998.

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21

Fortune, Michael A. Automated satellite-based estimates of precipitation: An assessment of accuracy. U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, National Environmental Satellite, Data, and Information Service, 1998.

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22

Fortune, Michael A. Automated satellite-based estimates of precipitation: An assessment of accuracy. U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, National Environmental Satellite, Data, and Information Service, 1998.

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23

United States. National Environmental Satellite, Data, and Information Service., ed. Automated satellite-based estimates of precipitation: An assessment of accuracy. U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, National Environmental Satellite, Data, and Information Service, 1998.

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24

Fortune, Michael A. Automated satellite-based estimates of precipitation: An assessment of accuracy. U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, National Environmental Satellite, Data, and Information Service, 1998.

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25

Hanson, R. Karl. The accuracy of recidivism risk assessments for sexual offenders: A meta-analysis. Public Safety and Emergency Preparedness Canada, 2007.

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26

G, Sigari, Costi T, Michigan State University. Division of Engineering Research., and United States. National Aeronautics and Space Administration., eds. Effect of accuracy of wind power prediction on power system operator: Final report. College of Engineering, Michigan State University, 1985.

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27

Barrionuevo, Jose M. A simple forecasting accuracy criterion under rational expectations: Evidence from the World Economic Outlook andTime seies models. International Monetary Fund, Research Department, 1992.

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28

G, Benjamin Stanley, and Forecast Systems Laboratory (U.S.), eds. A study of the accuracy of RUC-1 and RUC-2 wind and aircraft trajectory forecasts using ACARS observations. U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, Environmental Research Laboratories, Forecast Systems Laboratory, 1998.

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29

Office, General Accounting. Retirement forecasting: Evaluation of models shows need for information on forecast accuracy : report to the chairman, Subcommittee on Social Security and Income Maintenance Programs, Committee on Finance, United States Senate. The Office, 1986.

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30

Fund, International Monetary. A simple forecasting accuracy criterion under rational expectations: Evidence from the World economic outlook and time series models. International Monetary Fund, Research Department, 1992.

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31

Office, General Accounting. Short-term forecasting: Accuracy of USDA's meat forecasts and estimates : report to the Honorable J. Robert Kerrey, U.S. Senate. The Office, 1991.

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32

THORPEX: A Global Atmospheric Research Programme. THORPEX, A Global Atmospheric Research Programme: Accelerating improvements in the accuracy of one-day to two-week high-impact weather forecasts for the benefit of society, the economy, and the environment. World Meteorological Organization, 2004.

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33

United States. Congress. House. Committee on the Budget. CBO role and performance: Enhancing accuracy, reliability, and responsiveness in budget and economic estimates : hearing before the Committee on the Budget, House of Representatives, One Hundred Seventh Congress, second session, hearing held in Washington, DC, May 2, 2002. U.S. G.P.O., 2002.

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34

Office, United States Government Accountability. Depot maintenance: Persistent deficiencies limit accuracy and usefulness of DOD's funding allocation data reported to Congress : report to congressional committees. U.S. Government Accountability Office, 2005.

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35

United States. Government Accountability Office. Depot maintenance: Persistent deficiencies limit accuracy and usefulness of DOD's funding allocation data reported to Congress : report to congressional committees. U.S. Government Accountability Office, 2005.

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36

Robert, Kalish, ed. The weather revolution: Innovations and imminent breakthroughs in accurate forecasting. Plenum Press, 1994.

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37

Engle, R. F. Index-option pricing with stochastic volatility and the value of accurate variance forecasts. National Bureau of Economic Research, 1993.

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38

Verbeek, Jos. The World Bank's unified survey projections: How accurate are they? : an ex-post evaluation of US91-US97. World Bank, 1999.

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39

Shi, Yangyan. Evaluating Forecast Accuracy: Leading to Improve Forecasting Accuracy. LAP LAMBERT Academic Publishing, 2017.

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40

McCleary, Richard, David McDowall, and Bradley J. Bartos. Forecasting. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780190661557.003.0004.

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Chapter 4 downplays forecasting’s role in the design and analysis of time series experiments and emphasizes its potential abuses. While the “best” ARIMA model will outperform other forecasting models in the short and medium-run, long-horizon ARIMA forecasts grow increasingly inaccurate with diminished utility to the forecaster. Although the principles of forecasting help provide deeper insight into the nature of ARIMA models and modeling, the forecasts themselves are ordinarily of limited practical value. Forecasting can provide useful guidance to analysts choosing between two competing univar
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41

Kumar, Manmohan S. Forecasting Accuracy of Crude Oil Futures Prices. International Monetary Fund, 1991.

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42

Kumar, Manmohan S. Forecasting Accuracy of Crude Oil Futures Prices. International Monetary Fund, 1991.

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43

Kumar, Manmohan S. Forecasting Accuracy of Crude Oil Futures Prices. International Monetary Fund, 1991.

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44

Weather Forecasting Accuracy for FAA Traffic Flow Management. National Academies Press, 2003. http://dx.doi.org/10.17226/10637.

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45

Berger, Helge, Michael Ehrmann, and Marcel Fratzscher. Forecasting ECB Monetary Policy: Accuracy Is a Matter of Geography. International Monetary Fund, 2006.

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46

Berger, Helge, Michael Ehrmann, and Marcel Fratzscher. Forecasting Ecb Monetary Policy: Accuracy Is a Matter of Geography. International Monetary Fund, 2006.

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47

Berger, Helge, Michael Ehrmann, and Marcel Fratzscher. Forecasting Ecb Monetary Policy: Accuracy Is a Matter of Geography. International Monetary Fund, 2006.

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48

Kulcsar, Bela. The forecasting accuracy of univariate and structural time series models. Department of Economics, Loughborough University of Technology, 1992.

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49

Diemer, Sebastian. Real-Money vs. Play-Money Forecasting Accuracy in Online Prediction Markets. GRIN Publishing, 2013.

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50

Committee for a Workshop on Weather Forecasting Accuracy for FAA Traffic Control, Board on Atmospheric Sciences and Climate, Division on Earth and Life Studies, and National Research Council. Weather Forecasting Accuracy for FAA Traffic Flow Management: A Workshop Report. National Academies Press, 2003.

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