Panaretos, John and Psarakis, Stelios and Xekalaki, Evdokia and Karlis, Dimitris (2005): The Correlated GammaRatio Distribution in Model Evaluation and Selection. Published in: (2005)

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Abstract
The paper considers the problem of selecting one of two not necessarily nested competing regression models based on comparative evaluations of their abilities in each of two different issues: The first pertains to viewing the problem as a “bestfitting” model determination problem in the sense that a model is sought which is closest to the observed data, and utilizes some measure of the adequacy of the models to describe existing observations. The second is entirely different from the first in that it takes account of the predictive adequacy of the models.
It is shown that certain test statistics can be constructed which within each of the above settings can lead to appropriate model selection procedures based on sequential comparisons of the competing models in their abilities to describe the data or to predict future observations. The null distribution of these statistics, termed as the “Correlated Gamma Ratio Distribution”, is obtained as the distribution of the ratio of two correlated gamma variates. Applications are given as well as some simulation results revealing the behaviour of the model selection procedures developed. Potential extensions of the proposed procedures are described.
Item Type:  MPRA Paper 

Original Title:  The Correlated GammaRatio Distribution in Model Evaluation and Selection 
Language:  English 
Keywords:  Model selection, Bivariate gamma distribution, F distribution, Nonnested models, Predictive ability 
Subjects:  C  Mathematical and Quantitative Methods > C1  Econometric and Statistical Methods and Methodology: General 
Item ID:  6355 
Depositing User:  J Panaretos 
Date Deposited:  19. Dec 2007 07:26 
Last Modified:  21. Feb 2015 22:14 
URI:  https://mpra.ub.unimuenchen.de/id/eprint/6355 