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A parametric bootstrap approach for one-way classification model with skew-normal random effects 被引量:2
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作者 YE Ren-dao XU Li-jun +1 位作者 LUO Kun JIANG Ling 《Applied Mathematics(A Journal of Chinese Universities)》 SCIE CSCD 2019年第4期423-435,共13页
In this paper,several properties of one-way classification model with skew-normal random effects are obtained,such as moment generating function,density function and noncentral skew chi-square distribution,etc.Based o... In this paper,several properties of one-way classification model with skew-normal random effects are obtained,such as moment generating function,density function and noncentral skew chi-square distribution,etc.Based on the EM algorithm,we discuss the maximum likelihood(ML)estimation of unknown parameters.For testing problem of fixed effect,a parametric bootstrap(PB)approach is developed.Finally,some simulation results on the Type I error rates and powers of the PB approach are obtained,which show that the PB approach provides satisfactory performances on the Type I error rates and powers,even for small samples.For illustration,our main results are applied to a real data problem. 展开更多
关键词 PARAMETRIC BOOTSTRAP EM algorithm one-way classification model skew-NORMAL distribution skew chi-square distribution
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