Testing goodness of fit for a parametric family of link functions

doi:10.2307/2290868

淡江大學機構典藏 > 商管學院 > 統計學系暨研究所 > 期刊論文 > Item 987654321/20729

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題名:	Testing goodness of fit for a parametric family of link functions
作者:	Cheng, K. F.;吳忠武;Wu, Jong-wuu
貢獻者:	淡江大學統計學系
關鍵詞:	Consistency of the test;Dimension reduction;Link function;Quasi-likelihood model;Regression parameters
日期:	1994-06-01
上傳時間:	2009-11-30 12:57:58 (UTC+8)
出版者:	American Statistical Association
摘要:	We concern ourselves with the methods for testing the overall goodness of fit of a parametric family of link functions used for modeling the conditional mean of the response variable Y given the covariates X = x ∈ R P. The null hypothesis is that the conditional mean function is a known functional depending on βx and a finite number of parameters θ = (θ1,…, θq), where β is a p-dimensional row vector of regression parameters and x is a column vector. The proposed test statistic is derived from an “information” equivalence result and a dimension-reduction technique. The new test is very simple in computation. Also, it is generally consistent against broad class of alternatives and, asymptotically, the null distribution is independent of the underlying distribution of Y, given X = x. Practical examples are given to show the advantage of the proposed test. Furthermore, power comparisons with the test used by Su and Wei are also performed to indicate the usefulness of the new test. Particularly, we find that the new test has good power performance in discriminating between the probit and logit links.
關聯:	Journal of the American Statistical Association 89(426), pp.657-664
DOI:	10.2307/2290868
顯示於類別:	[統計學系暨研究所] 期刊論文

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