Bootstrapping the Probability Distribution of Peak Electricity Demand
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Other versions of this item:
- Veall, Michael R, 1987. "Bootstrapping the Probability Distribution of Peak Electricity Demand," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 28(1), pages 203-212, February.
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Cited by:
- Gregory, Allan W. & McCurdy, Thomas H., 1986. "The unbiasedness hypothesis in the forward foreign exchange market: A specification analysis with application to France, Italy, Japan, the United Kingdom and West Germany," European Economic Review, Elsevier, vol. 30(2), pages 365-381, April.
- MacKinnon, James G, 1992. "Model Specification Tests and Artificial Regressions," Journal of Economic Literature, American Economic Association, vol. 30(1), pages 102-146, March.
- Li, Hongyi & Maddala, G. S., 1997.
"Bootstrapping cointegrating regressions,"
Journal of Econometrics, Elsevier, vol. 80(2), pages 297-318, October.
- Tom Doan, "undated". "RATS program to demonstrate bootstrapping with cointegration," Statistical Software Components RTZ00021, Boston College Department of Economics.
- Allen, P. Geoffrey & Morzuch, Bernard J., 1995. "Comparing probability forecasts derived from theoretical distributions," International Journal of Forecasting, Elsevier, vol. 11(1), pages 147-157, March.
- Drago Papler & Štefan Bojnec, 2015. "Competitiveness and Factors of Delivery of Electricity," Faculty of Management Koper Monograph Series, University of Primorska, Faculty of Management Koper, number 978-961-266-188-5, June.
- Mohammed A. Al-Sahlawi, 1990. "Forecasting the Demand for Electricity in Saudi Arabia," The Energy Journal, , vol. 11(1), pages 119-126, January.
- Tonsor, Glynn T. & Dhuyvetter, Kevin C. & Mintert, James R., 2004. "Improving Cattle Basis Forecasting," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 29(2), pages 1-14, August.
- Grigoletto, Matteo, 1998. "Bootstrap prediction intervals for autoregressions: some alternatives," International Journal of Forecasting, Elsevier, vol. 14(4), pages 447-456, December.
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