Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1145667 | Journal of Multivariate Analysis | 2014 | 19 Pages |
Abstract
In a generalized linear model of binary data, we consider models based on a general link function including a logistic regression model and a probit model as special cases. For testing the null hypothesis H0H0 that the considered model is correct, we consider a family of ϕϕ-divergence goodness-of-fit test statistics CϕCϕ that includes a power divergence family of statistics RaRa. We propose a transformed CϕCϕ statistics that improves the speed of convergence to a chi-square limiting distribution and show numerically that the transformed RaRa statistic performs well. We also give a real data example of the transformed RaRa statistic being more reliable than the original RaRa statistic for testing H0H0.
Related Topics
Physical Sciences and Engineering
Mathematics
Numerical Analysis
Authors
Nobuhiro Taneichi, Yuri Sekiya, Jun Toyama,