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Document type:
Zeitschriftenaufsatz 
Author(s):
Czado, C., Gneiting, T., Held, L. 
Title:
Predictive model assessment for count data 
Abstract:
We discuss tools for the evaluation of probabilistic forecasts and the critique of statistical models for ordered discrete data. Our proposals include a non-randomized version of the probability integral transform, marginal calibration diagrams and proper scoring rules, such as the predictive deviance. In case studies, we critique count regression models for patent data, and assess the predictive performance of Bayesian age-period-cohort models for larynx cancer counts in Germany. 
Keywords:
Calibration; Forecast verification; Model diagnostics; Predictive deviance; Probability integral transform; Proper scoring rule; Ranked probability score. 
Journal title:
Biometrics 
Year:
2009 
Journal volume:
65 
Journal issue:
Pages contribution:
1254-1261 
Reviewed:
ja 
Language:
en 
Status:
Verlagsversion / published 
Semester:
SS 09 
Format:
Text