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线性模型中的独立性与拟合优度检验AI 解读

We consider a linear regression model and propose an omnibus test to simultaneously check the assumption of independence between the error and predictor variables and the goodness-of-fit of the parametric model. Our approach is based on testing for independence between the predictor and the residual obtained from the parametric fit by using the Hilbert–Schmidt independence criterion (Gretton et al., 2008). The proposed method requires no user-defined regularization, is…

剂量反应与回归中基于 p 值框架的阈值估计AI 解读

We use p-values to identify the threshold level at which a regression function leaves its baseline value, a problem motivated by applications in toxicological and pharmacological dose-response studies and environmental statistics. We study the problem in two sampling settings: one where multiple responses can be obtained at a number of different covariate levels, and the other the standard regression setting involving limited number of response values at each covariate. Our…

分析区间删失数据的伪似然方法AI 解读

We introduce a method based on a pseudolikelihood ratio for estimating the distribution function of the survival time in a mixed-case interval censoring model. In a mixed-case model, an individual is observed a random number of times, and at each time it is recorded whether an event has happened or not. One seeks to estimate the distribution of time to event. We use a Poisson process as the basis of a likelihood function to construct a pseudolikelihood ratio statistic for…