| 书目名称 | Smoothing Spline ANOVA Models |
| 编辑 | Chong Gu |
| 视频video | |
| 概述 | Covers latest research of smoothing methods in data analysis.Second edition is updated with latest computational methods, including the uses ofthe R package gss.Empirical studies are expanded, reorgan |
| 丛书名称 | Springer Series in Statistics |
| 图书封面 |  |
| 描述 | .Nonparametric function estimation with stochastic data, otherwise.known as smoothing, has been studied by several generations of.statisticians. Assisted by the ample computing power in today‘s.servers, desktops, and laptops, smoothing methods have been finding.their ways into everyday data analysis by practitioners. While scores.of methods have proved successful for univariate smoothing, ones.practical in multivariate settings number far less. Smoothing spline.ANOVA models are a versatile family of smoothing methods derived.through roughness penalties, that are suitable for both univariate and.multivariate problems..In this book, the author presents a treatise on penalty smoothing.under a unified framework. Methods are developed for (i) regression.with Gaussian and non-Gaussian responses as well as with censored lifetime data; (ii) density and conditional density estimation under a.variety of sampling schemes; and (iii) hazard rate estimation with.censored life time data and covariates. The unifying themes are the.general penalized likelihood method and the construction of.multivariate models with built-in ANOVA decompositions. Extensive.discussions are devoted to model constructi |
| 出版日期 | Book 2013Latest edition |
| 关键词 | ANOVA; ANOVA models; Spline smoothing; nonparametric smoothing; smoothing methods |
| 版次 | 2 |
| doi | https://doi.org/10.1007/978-1-4614-5369-7 |
| isbn_softcover | 978-1-4899-8984-0 |
| isbn_ebook | 978-1-4614-5369-7Series ISSN 0172-7397 Series E-ISSN 2197-568X |
| issn_series | 0172-7397 |
| copyright | Springer Science+Business Media New York 2013 |
发表于 2025-3-21 17:05:37
