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Comparative Evaluation of Categorical and Probabilistic Forecasts: Two Alternatives to the Traditional Approach

Allan H. MurphyDepartment of atmospheric Sciences, Oregon Stage University, Corvallis, OR 97331

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Abstract

Situations sometimes arise in which it is necessary to evaluate and compare the performance of categorical and probabilistic forecasts. The traditional approach to this problem involves the transformation of the probabilistic forecasts into categorical forecasts and the comparison of the two sets of forecasts in a categorical framework. This approach suffers from several serious deficiencies. Alternative approaches are proposed here that consist in (i) treating the categorical forecasts as probabilistic forecasts or (ii) replacing the categorical forecasts with primitive probabilistic forecasts. These approaches permit the sets of forecasts to be compared in a probabilistic framework and offer several important advantages vis-a-vis the traditional approach. The proposed approaches are compared and some issues related to these approaches and the overall problem itself are discussed.

Abstract

Situations sometimes arise in which it is necessary to evaluate and compare the performance of categorical and probabilistic forecasts. The traditional approach to this problem involves the transformation of the probabilistic forecasts into categorical forecasts and the comparison of the two sets of forecasts in a categorical framework. This approach suffers from several serious deficiencies. Alternative approaches are proposed here that consist in (i) treating the categorical forecasts as probabilistic forecasts or (ii) replacing the categorical forecasts with primitive probabilistic forecasts. These approaches permit the sets of forecasts to be compared in a probabilistic framework and offer several important advantages vis-a-vis the traditional approach. The proposed approaches are compared and some issues related to these approaches and the overall problem itself are discussed.

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