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The complexity of forecast testing

The complexity of forecast testing Consider a weather forecaster predicting the probability of rain for the next day. We consider tests that given a finite sequence of forecast predictions and outcomes will either pass or fail the forecaster. It is known that any test which passes a forecaster who knows the distribution of nature can also be probabilistically passed by a forecaster with no knowledge of future events. This note summarizes and examines the computational complexity of such forecasters. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ACM SIGecom Exchanges Association for Computing Machinery

The complexity of forecast testing

ACM SIGecom Exchanges , Volume 7 (3) – Nov 1, 2008

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Publisher
Association for Computing Machinery
Copyright
Copyright © 2008 by ACM Inc.
ISSN
1551-9031
DOI
10.1145/1486877.1486885
Publisher site
See Article on Publisher Site

Abstract

Consider a weather forecaster predicting the probability of rain for the next day. We consider tests that given a finite sequence of forecast predictions and outcomes will either pass or fail the forecaster. It is known that any test which passes a forecaster who knows the distribution of nature can also be probabilistically passed by a forecaster with no knowledge of future events. This note summarizes and examines the computational complexity of such forecasters.

Journal

ACM SIGecom ExchangesAssociation for Computing Machinery

Published: Nov 1, 2008

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