期刊名称：Sankhya. Series A, mathematical statistics and probability
印刷版ISSN：0976-836X
电子版ISSN：0976-8378
出版年度：2005
卷号：67
期号：03
出版社：Indian Statistical Institute
摘要：The SiZer Map, proposed by Chaudhuri and Marron (1999), is a statistical tool for finding which features in noisy data are strong enough to be distinguished from background noise. In this paper, we propose the local likelihood SiZer map. Some simulation examples illustrate that the newly proposed SiZer map is more efficient in distinguishing features than the original one, because of the inferential advantage of the local likelihood approach. Some computational problems are addressed, with the result that the computational cost in constructing the local likelihood SiZer map is close to that of the original one.
关键词：Confidence bands, generalized linear models, local polynomials, local likelihood, quasi-likelihood, significant features, SiZer map.
