Generalized linear models in planning practiceL.G OBrien
penalized Generalized Linear Models; (2) We provide a feasible weighted nodewise regression proof which generalizes the results in the literature; (3) We realize that norms used in feasible nodewise regression proofs should be weaker or equal to the norms in penalized Generalized Linear Model loss...
摘要: The is written for the practicing actuary who would like to understand generalized linear models (GLMs) and use them to analyze insurance data. The guide is divided into three sections.被引量: 66 年份: 2004 收藏 引用 批量引用 报错 分享 全部来源 免费下载 求助全文 Semantic Scholar (...
Generalized linear models are extensions of the linear regression model described in the previous chapter. In particular, they avoid the selection of a single transformation of the data that must achieve the possibly conflicting goals of normality and linearity imposed by the linear regression model, ...
Generalized linear models (GLMs) are gaining popularity as a statistical analysis method for insurance data. We study the theory and applications of GLMs in insurance. The first chapter gives an introduction of the theory of GLMs and generalized linear mixed models (GLMMs) as well as the bias ...
Generalized linear models are fit using the glm( ) function. The form of the glm function is glm(formula , family= familytype(link=linkfunction), data=) Family Default Link Function binomial (link = "logit") gaussian (link = "identity") Gamma (link = "inverse") inverse.gaussian (link ...
Combining a modern, data-analytic perspective with a focus on applications in the social sciences, the Second Edition of Applied Regression Analysis and Generalized Linear Models provides in-depth coverage of regression analysis, generalized linear models, and closely related methods. Although the text ...
Linear Prediction and Regression Likelihood Methods Unbiased Estimating Equations Quasilikelihood and Variance Function Models (QVF) Generalized Linear Models Bootstrap Methods Appendix B: Technical Details Appendix to Chapter 1: Power in Berkson... R Carroll - Chapman & Hall/CRC 被引量: 2276发表: ...
By starting from a natural class of robust estimators for generalized linear models based on the notion of quasi-likelihood, we define robust deviances that can be used for stepwise model selection as in the classical framework. We derive the asymptotic distribution of tests based on robust devian...
Adjustment for non-differential misclassification error in the generalized linear model. We propose a method to adjust for misclassification in covariates when one applies the generalized linear model. In the case where one can observe some ... X Liu,KY Liang - 《Statistics in Medicine》 被引量...