An optimal test for the mean function hypothesis

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题名:	An optimal test for the mean function hypothesis
作者:	Cheng,KF;Wu,JW
贡献者:	統計研究所
关键词:	GENERALIZED LINEAR-MODELS;REGRESSION-MODELS
日期:	1998
上传时间:	2010-06-29 19:33:39 (UTC+8)
出版者:	中央大學
摘要:	The conditional mean of the response variable Y given the covariates X = x is an element of R-p is usually modelled by a parametric function g(beta x), where g(.) is a known function and beta is a row vector of p unknown parameters. In this paper, a new method for testing the goodness of fit of the model g(beta x) for the mean function is presented. The new test depends on the selection of weight functions. An expression for the efficacy of the proposed test under a sequence of local alternatives will be given. With the application of this result one can direct the choice of the optimal weight functions in order to maximize the efficacy. The new test is simple in computation and consistent against a broad class of alternatives. Asymptotically, the null distribution is independent of the underlying distribution of Y given X = x. Two pratical examples are given to illustrate the method. Further, simulation studies are given to show the advantages of the proposed test.
關聯:	STATISTICA SINICA
显示于类别:	[統計研究所] 期刊論文

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