论文检索

设计实验中失拟检验的功效：样本量与重复观测分配指南AI 解读

Although there exists substantial literature on lack-of-fit tests for normal linear models, there is scant literature for determining the number or distribution of points to replicate when starting with an un-replicated base design like a factorial, response surface, or related constructions. In this article, we provide an easy-to-implement approach to determining power and sample size based on the standard lack-of-fit test. The method employs simply stated bounds on the…

不依赖模型形式的变量选择AI 解读

Summary The importance of variable selection in regression has grown in recent years as computing power has encouraged the modelling of data sets of ever-increasing size. Data mining applications in finance, marketing and bioinformatics are obvious examples. A limitation of nearly all existing variable selection methods is the need to specify the correct model before selection. When the number of predictors is large, model formulation and validation can be difficult or even…

通过重加权使回归协变量呈椭圆对称分布AI 解读

We investigate a method of constructing weights to induce elliptically contoured covariates in regression analyses. Much recent work in regression has identified various data analytic and model robustness advantages associated with such covariates. In particular, new estimation methods like SIR, SIRII, SAVE, and PHD have been built around the assumption of elliptically contoured covariates. Finite samples of regression covariates may deviate from this ideal in practice, and…

一类新的多元分布及其在蒙特卡洛研究中的应用AI 解读

We consider a new class of multivariate probability distributions having representation X = RLY (p), where R is distributed as √χ 2 (p), L is the Choleski factorization of the scaling matrix Σ, and Y (p) represents an arbitrary distribution on the p-dimensional unit hypersphere. If Y (p) is uniform, then X has a multivariate normal distribution with mean 0 and covariance matrix Σ. The use of classical spherical distributions or other nonuniform distributions for Y (p) leads…