期刊
COMPUTATIONAL STATISTICS & DATA ANALYSIS
卷 50, 期 1, 页码 61-76出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.csda.2004.07.008
关键词
B-splines; difference penalty; multidimensional array; P-splines; smoothing; tensor product
A framework of penalized generalized linear models and tensor products of B-splines with roughness penalties allows effective smoothing of data in multidimensional arrays. A straightforward application of the penalized Fisher scoring algorithm quickly runs into storage and computational difficulties. A novel algorithm takes advantage of the special structure of both the data as an array and the model matrix as a tenser product; the algorithm is fast, uses only a moderate amount of memory and works for any number of dimensions. Examples are given of how the method is used to smooth life tables and image data. (c) 2004 Elsevier B.V. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据