Bibliography

Armstrong, J S, ed. 2001. Principles of Forecasting: A Handbook for Researchers and Practitioners. Kluwer Academic Publishers.

Armstrong, J Scott. 1985. Long-Range Forecasting: From Crystal Ball to Computer. John Wiley & Sons.

Athanasopoulos, George, Roman A Ahmed, and Rob J Hyndman. 2009. “Hierarchical Forecasts for Australian Domestic Tourism.” International Journal of Forecasting 25: 146–66. https://doi.org/10.1016/j.ijforecast.2008.07.004.

Athanasopoulos, George, and Rob J Hyndman. 2008. “Modelling and Forecasting Australian Domestic Tourism.” Tourism Management 29 (1): 19–31.

Athanasopoulos, George, Rob J Hyndman, Nikolaos Kourentzes, and Fotios Petropoulos. 2017. “Forecasting with Temporal Hierarchies.” European Journal of Operational Research 262 (1): 60–74.

Athanasopoulos, G, D S Poskitt, and F Vahid. 2012. “Two Canonical VARMA Forms: Scalar Component Models Vis-à-Vis the Echelon Form.” Econometric Reviews 31 (1): 60–83.

Bates, J M, and C W J Granger. 1969. “The Combination of Forecasts.” Operational Research Quarterly 20 (4): 451–68. https://doi.org/10.1057/jors.1969.103.

Bergmeir, Christoph, Rob J Hyndman, and José M Benítez. 2016. “Bagging Exponential Smoothing Methods Using STL Decomposition and Box-Cox Transformation.” International Journal of Forecasting 32 (2): 303–12.

Bergmeir, Christoph, Rob J Hyndman, and Bonsoo Koo. 2018. “A Note on the Validity of Cross-Validation for Evaluating Autoregressive Time Series Prediction.” Computational Statistics and Data Analysis 120: 70–83. https://robjhyndman.com/publications/cv-time-series/.

Box, George E P, and Gwilym M Jenkins. 1970. Time Series Analysis: Forecasting and Control. San Francisco: Holden-Day.

Box, George E P, Gwilym M Jenkins, Gregory C Reinsel, and Greta M Ljung. 2015. Time Series Analysis: Forecasting and Control. 5th ed. Hoboken, New Jersey: John Wiley & Sons.

Brockwell, Peter J, and Richard A Davis. 2016. Introduction to Time Series and Forecasting. 3rd ed. New York, USA: Springer.

Brown, Robert Goodell. 1959. Statistical Forecasting for Inventory Control. McGraw/Hill.

Buehler, Roger, Deanna Messervey, and Dale Griffin. 2005. “Collaborative Planning and Prediction: Does Group Discussion Affect Optimistic Biases in Time Estimation?” Organizational Behavior and Human Decision Processes 97 (1): 47–63.

Christou, Vasiliki, and Konstantinos Fokianos. 2015. “On Count Time Series Prediction.” Journal of Statistical Computation and Simulation 85 (2): 357–73.

Clemen, R. 1989. “Combining Forecasts: A Review and Annotated Bibliography with Discussion.” International Journal of Forecasting 5: 559–608.

Cleveland, Robert B, William S Cleveland, Jean E McRae, and Irma J Terpenning. 1990. “STL: A Seasonal-Trend Decomposition Procedure Based on Loess.” Journal of Official Statistics 6 (1): 3–73.

Cleveland, William S. 1993. Visualizing Data. Hobart Press.

Crone, Sven F, Michele Hibon, and Konstantinos Nikolopoulos. 2011. “Advances in Forecasting with Neural Networks? Empirical Evidence from the NN3 Competition on Time Series Prediction.” International Journal of Forecasting 27 (3): 635–60.

Croston, John D. 1972. “Forecasting and Stock Control for Intermittent Demands.” Operational Research Quarterly 23 (3): 289–303.

Dagum, Estela Bee, and Silvia Bianconcini. 2016. Seasonal Adjustment Methods and Real Time Trend-Cycle Estimation. Springer.

De Livera, Alysha M, Rob J Hyndman, and Ralph D Snyder. 2011. “Forecasting Time Series with Complex Seasonal Patterns Using Exponential Smoothing.” J American Statistical Association 106 (496): 1513–27.

Eroglu, Cuneyt, and Keely L Croxton. 2010. “Biases in Judgmental Adjustments of Statistical Forecasts: The Role of Individual Differences.” International Journal of Forecasting 26 (1): 116–33.

Fan, Shu, and Rob J Hyndman. 2012. “Short-Term Load Forecasting Based on a Semi-Parametric Additive Model.” IEEE Transactions on Power Systems 27 (1): 134–41.

Fildes, Robert, and Paul Goodwin. 2007a. “Against Your Better Judgment? How Organizations Can Improve Their Use of Management Judgment in Forecasting.” Interfaces 37 (6): 570–76.

———. 2007b. “Good and Bad Judgment in Forecasting: Lessons from Four Companies.” Foresight: The International Journal of Applied Forecasting, no. 8: 5–10.

Franses, Philip Hans, and Rianne Legerstee. 2013. “Do Statistical Forecasting Models for SKU-Level Data Benefit from Including Past Expert Knowledge?” International Journal of Forecasting 29 (1): 80–87.

Gardner, Everette S. 1985. “Exponential Smoothing: The State of the Art.” Journal of Forecasting 4 (1): 1–28.

———. 2006. “Exponential Smoothing: The State of the Art — Part II.” Interantional Journal of Forecasting 22: 637–66.

Gardner, Everette S, and Ed McKenzie. 1985. “Forecasting Trends in Time Series.” Management Science 31 (10): 1237–46.

Goodwin, Paul, and George Wright. 2009. Decision Analysis for Management Judgment. 4th ed. Chichester: John Wiley & Sons.

Green, Kesten C., and J Scott Armstrong. 2007. “Structured Analogies for Forecasting.” International Journal of Forecasting 23 (3): 365–76.

Gross, C W, and J E Sohl. 1990. “Disaggregation Methods to Expedite Product Line Forecasting.” Journal of Forecasting 9: 233–54.

Groves, Robert M., Floyd J. Fowler, Mick P. Couper, James M. Lepkowski, Eleanor Singer, and Roger Tourangeau. 2009. Survey Methodology. 2nd ed. John Wiley & Sons.

Hamilton, J D. 1994. Time Series Analysis. Princeton University Press, Princeton.

Harrell, Frank E. 2015. Regression Modeling Strategies: With Applications to Linear Models, Logistic and Ordinal Regression, and Survival Analysis. 2nd ed. New York, USA: Springer.

Harris, Richard, and Robert Sollis. 2003. Applied Time Series Modelling and Forecasting. Chichester, UK: John Wiley & Sons.

Harvey, Nigel. 2001. “Improving Judgment in Forecasting.” In Principles of Forecasting: A Handbook for Researchers and Practitioners, edited by J Scott Armstrong, 59–80. Boston, MA: Kluwer Academic Publishers.

Holt, Charles E. 1957. “Forecasting Seasonals and Trends by Exponentially Weighted Averages.” O.N.R. Memorandum 52. Carnegie Institute of Technology, Pittsburgh USA.

Hyndman, Rob J, Roman A Ahmed, George Athanasopoulos, and Han Lin Shang. 2011. “Optimal Combination Forecasts for Hierarchical Time Series.” Computational Statistics and Data Analysis 55 (9): 2579–89. https://doi.org/10.1016/j.csda.2011.03.006.

Hyndman, Rob J, and Shu Fan. 2010. “Density Forecasting for Long-Term Peak Electricity Demand.” IEEE Transactions on Power Systems 25 (2): 1142–53.

Hyndman, Rob J, and Yeasmin Khandakar. 2008. “Automatic Time Series Forecasting: The Forecast Package for R.” Journal of Statistical Software 27 (1): 1–22. https://www.jstatsoft.org/article/view/v027i03.

Hyndman, Rob J, and Anne B Koehler. 2006. “Another Look at Measures of Forecast Accuracy.” International Journal of Forecasting 22: 679–88.

Hyndman, Rob J, Anne B Koehler, J Keith Ord, and Ralph D Snyder. 2008. Forecasting with Exponential Smoothing: The State Space Approach. Berlin: Springer-Verlag. http://www.exponentialsmoothing.net.

Hyndman, Rob J, Anne B Koehler, Ralph D Snyder, and Simone Grose. 2002. “A State Space Framework for Automatic Forecasting Using Exponential Smoothing Methods.” International Journal of Forecasting 18 (3): 439–54.

Hyndman, Rob J, Alan Lee, and Earo Wang. 2016. “Fast Computation of Reconciled Forecasts for Hierarchical and Grouped Time Series.” Computational Statistics and Data Analysis 97: 16–32.

James, Gareth, Daniela Witten, Trevor Hastie, and Robert Tibshirani. 2014. An Introduction to Statistical Learning: With Applications in R. New York: Springer.

Kahn, Kenneth B. 2006. New Product Forecasting: An Applied Approach. M.E. Sharp.

Kahneman, D., and D Lovallo. 1993. “Timid Choices and Bold Forecasts: A Cognitive Perspective on Risk Taking.” Management Science 39 (1): 17–31.

Kwiatkowski, Denis, Peter C B Phillips, Peter Schmidt, and Yongcheol Shin. 1992. “Testing the Null Hypothesis of Stationarity Against the Alternative of a Unit Root: How Sure Are We That Economic Time Series Have a Unit Root?” Journal of Econometrics 54 (1-3): 159–78.

Lahiri, Soumendra Nath. 2013. Resampling Methods for Dependent Data. New York, USA: Springer Science & Business Media.

Lawrence, Michael, Paul Goodwin, Marcus O’Connor, and Dilek Önkal. 2006. “Judgmental Forecasting: A Review of Progress over the Last 25 Years.” International Journal of Forecasting 22 (3): 493–518.

Lütkepohl, H. 2005. New Introduction to Multiple Time Series Analysis. Berlin: Springer-Verlag.

———. 2007. “General-to-Specific or Specific-to-General Modelling? An Opinion on Current Econometric Terminology.” Journal of Econometrics 136: 234–319.

Morwitz, Vicki G., Joel H. Steckel, and Alok Gupta. 2007. “When Do Purchase Intentions Predict Sales?” International Journal of Forecasting 23 (3): 347–64.

Ord, J Keith, Robert Fildes, and Nikolaos Kourentzes. 2017. Principles of Business Forecasting. 2nd ed. Wessex Press Publishing Co.

Önkal, Dilek, Kadire Zeynep Sayim, and Mustafa Sinan Gönül. 2012. “Scenarios as Channels of Forecast Advice.” Technological Forecasting and Social Change 80: 772–88.

Pankratz, Alan E. 1991. Forecasting with Dynamic Regression Models. New York, USA: John Wiley & Sons.

Pegels, C C. 1969. “Exponential Smoothing: Some New Variations.” Management Science 12: 311–15.

Peña, Daniel, George C Tiao, and Ruey S Tsay, eds. 2001. A Course in Time Series Analysis. New York, USA: John Wiley & Sons.

Pfaff, Bernhard. 2008. Analysis of Integrated and Cointegrated Time Series with R. New York, USA: Springer Science & Business Media.

Randall, Donna M, and James A Wolff. 1994. “The Time Interval in the Intention-Behaviour Relationship: Meta-Analysis.” British Journal of Social Psychology 33: 405–18.

Rowe, Gene. 2007. “A Guide to Delphi.” Foresight: The International Journal of Applied Forecasting, no. 8: 11–16.

Rowe, Gene, and George Wright. 1999. “The Delphi Technique as a Forecasting Tool: Issues and Analysis.” International Journal of Forecasting 15: 353–75.

Sanders, Nada, Paul Goodwin, Dilek Önkal, Mustafa Sinan Gönül, Nigel Harvey, Anthony Lee, and Lucy Kjolso. 2005. “When and How Should Statistical Forecasts Be Judgmentally Adjusted?” Foresight: The International Journal of Applied Forecasting 1 (1): 5–23.

Sheather, Simon J. 2009. A Modern Approach to Regression with R. New York, USA: Springer.

Shenstone, Lydia, and Rob J Hyndman. 2005. “Stochastic Models Underlying Croston’s Method for Intermittent Demand Forecasting.” Journal of Forecasting 24 (6): 389–402. https://dx.doi.org/10.1002/for.963.

Taylor, J W. 2003. “Exponential Smoothing with a Damped Multiplicative Trend.” International Journal of Forecasting 19: 715–25.

Theodosiou, Marina. 2011. “Forecasting Monthly and Quarterly Time Series Using STL Decomposition.” International Journal of Forecasting 27 (4): 1178–95.

Unwin, Antony. 2015. Graphical Data Analysis with R. Chapman; Hall/CRC.

Wang, Xiaozhe, Kate A. Smith, and Rob J Hyndman. 2006. “Characteristic-Based Clustering for Time Series Data.” Data Mining and Knowledge Discovery 13 (3): 335–64.

Wickham, Hadley. 2016. ggplot2: Elegant Graphics for Data Analysis. 2nd ed. Springer.

Wickramasuriya, Shanika L, George Athanasopoulos, and Rob J Hyndman. 2018. “Optimal Forecast Reconciliation for Hierarchical and Grouped Time Series Through Trace Minimization.” J American Statistical Association to appear. https://robjhyndman.com/publications/mint/.

Winters, P R. 1960. “Forecasting Sales by Exponentially Weighted Moving Averages.” Management Science 6: 324–42.