Results 261 to 270 of about 604,354 (307)
Journal of Monetary Economics, 1999 This paper investigates forecasts of U.S. inflation at the 12-month horizon. The starting point is the conventional unemployment rate Phillips curve, which is examined in a simulated out of sample forecasting framework. Inflation forecasts produced by the Phillips curve generally have been more accurate than forecasts based on other macroeconomic ...
James H. Stock, Mark W. Watson
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SSRN Electronic Journal, 2010
AbstractThis article studies two issues in forecast combination, first considering ways to combine forecasts from surveys and time series models. Second, it considers the possibility, advanced by Hendry and Clements (2004), that model instability can help explain the gains in forecasting performance resulting from combination.
Marco Aiolfi +2 more
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AbstractThis article studies two issues in forecast combination, first considering ways to combine forecasts from surveys and time series models. Second, it considers the possibility, advanced by Hendry and Clements (2004), that model instability can help explain the gains in forecasting performance resulting from combination.
Marco Aiolfi +2 more
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Science, 2016
Police are turning to big data to stop crime before it happens. But is predictive policing biased—and does it even work?
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Police are turning to big data to stop crime before it happens. But is predictive policing biased—and does it even work?
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2011
Suggested Citation: Armstrong, J.S., Green, K.C. and Graefe, A. "Forecasting Principles." In International Encyclopedia of Statistical Science (Ed. M. Lovric). Springer, 2011.
Armstrong, J. Scott +2 more
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Suggested Citation: Armstrong, J.S., Green, K.C. and Graefe, A. "Forecasting Principles." In International Encyclopedia of Statistical Science (Ed. M. Lovric). Springer, 2011.
Armstrong, J. Scott +2 more
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Forecasting Inflation Forecast Errors [PDF]
, 2008 We evaluate inflation forecasts from the Survey of Professional Forecasters (SPF) of the Central Bank of Chile. Forecast errors for the period 2000-2008 show an excess of autocorrelation and a statistically significant bias at the end of the sample. We take advantage of the autocorrelation structure of the forecast errors to build new and more accurate
Andrea Betancor, Pablo Pincheira
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Climacteric, 2015
Recent epidemiological studies from various countries point at the mounting incidence of cancer. This continuous increase in the number of cancer cases will keep its pace in the future. The lifetime risk of cancer for people born since 1960 is forecast to be more than 50%.
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Recent epidemiological studies from various countries point at the mounting incidence of cancer. This continuous increase in the number of cancer cases will keep its pace in the future. The lifetime risk of cancer for people born since 1960 is forecast to be more than 50%.
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Microfounded Forecasting [PDF]
, 2014 In this paper, we propose a microfounded framework to investigate a panel of forecasts (e.g. model-driven or survey-based) and the possibility to improve their out-of-sample forecast performance by employing a bias-correction device. Following Patton and Timmermann (2007), we theoretically justify the modeling of forecasts as function of the ...
Gaglianone, Wagner Piazza +1 more
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2009
Schon seit mehreren Jahrzehnten wird bei meisten Unternehmen Performance Tuning von Rechnersystemen betrieben. Dieses Thema wurde wie von der Seite der Unternehmen als auch von der Wissenschaft mittlerweile in zahlreichen unterschiedlichen Aspekten erforscht und ausgearbeitet.
Tropmann-Frick, Marina +2 more
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Schon seit mehreren Jahrzehnten wird bei meisten Unternehmen Performance Tuning von Rechnersystemen betrieben. Dieses Thema wurde wie von der Seite der Unternehmen als auch von der Wissenschaft mittlerweile in zahlreichen unterschiedlichen Aspekten erforscht und ausgearbeitet.
Tropmann-Frick, Marina +2 more
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Science
“AI-Powered Forecasting” was recently on the cover of Science , highlighting a new deep learning model for much faster and more accurate weather forecasting. Known as GraphCast, it outperformed the gold-standard system and had an accuracy of 99.7% for
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“AI-Powered Forecasting” was recently on the cover of Science , highlighting a new deep learning model for much faster and more accurate weather forecasting. Known as GraphCast, it outperformed the gold-standard system and had an accuracy of 99.7% for
openaire +2 more sources