Testing the hypothesis of a generalized linear regression model using nonparametric regression estimation
✍ Scribed by M.Celia Rodríguez-Campos; Wenceslao González-Manteiga; Ricardo Cao
- Publisher
- Elsevier Science
- Year
- 1998
- Tongue
- English
- Weight
- 891 KB
- Volume
- 67
- Category
- Article
- ISSN
- 0378-3758
No coin nor oath required. For personal study only.
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## Abstract Consider the two linear regression models of __Y__~__ij__~ on __X__~__ij__~, namely __Y__~__ij__~ = β~__io__~ + β~__ij__~, __X__~__ij__~ + __E__~__ij__~ = 1, 2,…, __n__~__i__~, __i__ = 1, 2, where __E__~__ij__~ are assumed to be normally distributed with zero mean and common unknown var
For the problem of checking linearity in a heteroscedastic nonparametric regression model under a ÿxed design assumption, we study maximin designs which maximize the minimum power of a nonparametric test over a broad class of alternatives from the assumed linear regression model. It is demonstrated