Testing additivity in nonparametric regression under random censorship
β Scribed by Mohammed Debbarh; Vivian Viallon
- Book ID
- 108267572
- Publisher
- Elsevier Science
- Year
- 2008
- Tongue
- English
- Weight
- 605 KB
- Volume
- 78
- Category
- Article
- ISSN
- 0167-7152
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π SIMILAR VOLUMES
This paper considers large sample inference for the regression parameter in a partly linear model for right censored data. We introduce an estimated empirical likelihood for the regression parameter and show that its limiting distribution is a mixture of central chi-squared distributions. A Monte Ca
We use U-statistic-type processes to detect a possible change in the distribution of the observations under random censorship. We obtain weighted approximations for the U-statistic-type processes in case of symmetric as well as antisyrnmetric kernels. Several limit theorems are derived under the 'no