Accession Number : ADA478635


Title :   Predictive Model Assessment for Count Data


Corporate Author : WASHINGTON UNIV SEATTLE DEPT OF STATISTICS


Personal Author(s) : Czado, Claudia ; Gneiting, Tilmann ; Held, Leonhard


Full Text : http://www.dtic.mil/dtic/tr/fulltext/u2/a478635.pdf


Report Date : 05 Sep 2007


Pagination or Media Count : 20


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. Key words: Calibration; Forecast veri cation; Model diagnostics; Predictive deviance; Probability integral transform; Proper scoring rule; Ranked probability score.


Descriptors :   *MATHEMATICAL MODELS , *FORECASTING , *STATISTICAL ANALYSIS , PROBABILITY , CASE STUDIES , DIAGNOSIS(GENERAL) , INTEGRAL TRANSFORMS , LARYNX , PATENTS , CANCER , SCORING , CALIBRATION , GERMANY , REGRESSION ANALYSIS , COUNTING METHODS


Subject Categories : Meteorology
      Statistics and Probability


Distribution Statement : APPROVED FOR PUBLIC RELEASE