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	Provedor de dados 31 (1) Autor Brorsen, B. Wade (1) Lusk, Jayson L. (1) Norwood, F. Bailey (1) Palavra-chave Agribusiness (1) Discrete dependent variables (1) Forecasting (1) Likelihood functions (1) Model selection (1) Out-of-sample (1) Quality grades (1) Receiver-operator curves (1) Mais... Tipo do documento Journal Article (1) Ano 2004 (1) País United States (1) Idioma Inglês (1)		Ordenar por:  Relevância Autor Título Ano Registros recuperados: 1 Primeira ... 1 ... Última Model Selection for Discrete Dependent Variables: Better Statistics for Better Steaks 31 Norwood, F. Bailey; Lusk, Jayson L.; Brorsen, B. Wade. Little research has been conducted on evaluating out-of sample forecasts of discrete dependent variables. This study describes the large and small sample properties of two forecast evaluation techniques for discrete dependent variables: receiver-operator curves and out-of-sample log-likelihood functions. The methods are shown to provide identical model rankings in large samples and similar rankings in small samples. The likelihood function method is better at detecting forecast accuracy in small samples. By improving forecasts of fed cattle quality grades, the forecast evaluation methods are shown to increase cattle marketing revenues by $2.59/head. Tipo: Journal Article Palavras-chave: Discrete dependent variables; Forecasting; Likelihood functions; Model selection; Out-of-sample; Quality grades; Receiver-operator curves; Agribusiness. Ano: 2004 URL: http://purl.umn.edu/30912 Registros recuperados: 1 Primeira ... 1 ... Última

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