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统计拓扑与随机星际介质AI 解读

We use topological methods to investigate the small-scale variation and local spatial characteristics of the interstellar medium (ISM) in three regions of the southern sky. We demonstrate that there are circumstances where topological methods can identify differences in distributions when conventional marginal or correlation analyses may not. We propose a nonparametric method for comparing two fields based on the counts of topological features and the geometry of the…

重复测量与事件时间结局的联合建模：灵活设定与精确似然推断AI 解读

Summary Random effects or shared parameter models are commonly advocated for the analysis of combined repeated measurement and event history data, including dropout from longitudinal trials. Their use in practical applications has generally been limited by computational cost and complexity, meaning that only simple special cases can be fitted by using readily available software. We propose a new approach that exploits recent distributional results for the extended skew…

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相对风险回归中的残差图AI 解读

Martingale-based residuals proposed for proportional hazards regression by Barlow & Prentice (1988) are considered. Plots of such residuals against time are shown to exhibit systematic patterns which are not a priori predictable even when the model is appropriate. For the plots to be fully useful therefore account needs to be taken of the expected pattern under the model. A simple amendment is suggested.

危险率变点模型中似然比检验的一个问题AI 解读

A likelihood ratio test for constant hazard against a step change alternative has received considerable attention in recent years. Additional information in the maximum likelihood estimate of the change-point can seriously affect interpretation of test results. Some simple modifications are considered for which exact percentage points can be derived. Monte Carlo power and mean squared error comparisons are encouraging.

变点风险率模型似然比检验的一个问题AI 解读

A likelihood ratio test for constant hazard against a step change alternative has received considerable attention in recent years. Additional information in the maximum likelihood estimate of the change-point can seriously affect interpretation of test results. Some simple modifications are considered for which exact percentage points can be derived. Monte Carlo power and mean squared error comparisons are encouraging.