A goodness-of-fit test for logistic-normal models using nonparametric smoothing method
β Scribed by Kuo-Chin Lin; Yi-Ju Chen
- Book ID
- 108193501
- Publisher
- Elsevier Science
- Year
- 2011
- Tongue
- English
- Weight
- 189 KB
- Volume
- 141
- Category
- Article
- ISSN
- 0378-3758
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π SIMILAR VOLUMES
We derive a nonparametric test for discriminating between generalized autoregressive models. This test is a modiΓΏcation of the nonparametric tests proposed in Diebolt and Ngatchou Wandji (PrΓ epublications MathΓ ematiques de l'UniversitΓ e Paris-Nord, vol. 96-04) and Diebolt et al. (Scand. J. Statis
Recent work has shown that there may be disadvantages in the use of the chi-square-like goodness-of-fit tests for the logistic regression model proposed by Hosmer and Lemeshow that use fixed groups of the estimated probabilities. A particular concern with these grouping strategies based on estimated