Model Selection for Discrete Dependent Variables: Better Statistics for Better Steaks

Model Selection for Discrete Dependent Variables: Better Statistics for Better Steaks

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 funct...

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Bibliographic Details
Main Authors: F. Bailey Norwood, Jayson L. Lusk, B. Wade Brorsen
Format: Article
Language:English
Published: Western Agricultural Economics Association 2004-12-01
Series:Journal of Agricultural and Resource Economics
Subjects:
discrete dependent variables
forecasting
likelihood functions
model selection
out-of-sample
quality grades
receiver-operator curves
Online Access:https://ageconsearch.umn.edu/record/30912

Internet

https://ageconsearch.umn.edu/record/30912

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