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高维回归中的推断AI 解读

Abstract This paper develops an approach to inference in a linear regression model when the number of potential explanatory variables is larger than the sample size. The approach treats each regression coefficient in turn as the interest parameter, the remaining coefficients being nuisance parameters, and seeks an optimal interest-respecting transformation, inducing sparsity on the relevant blocks of the notional Fisher information matrix. The induced sparsity is exploited…

复合似然推断的模型设定检验AI 解读

Summary Composite likelihood functions are often used for inference in applications where the data have a complex structure. While inference based on the composite likelihood can be more robust than inference based on the full likelihood, the inference is not valid if the associated conditional or marginal models are misspecified. In this paper, we propose a general class of specification tests for composite likelihood inference. The test statistics are motivated by the fact…

高维情形下的修正似然根AI 解读

Summary We examine a higher order approximation to the significance function with increasing numbers of nuisance parameters, based on the normal approximation to an adjusted log-likelihood root. We show that the rate of the correction for nuisance parameters is larger than the correction for non-normality, when the parameter dimension p is O(nα) for α<12. We specialize the results to linear exponential families and location–scale families and illustrate these with…

统计理论与建模：纪念 David Cox 爵士AI 解读

Part 1 Statistical theory - theoretical concepts significance tests theory of optimal tests estimation asymptotic theory. Part 2 Applied statistics - preliminary considerations statistical models statistical inference model adequancy exploratory and robust methods multi-variate methods use of computers. Part 3 Generalized linear models - a class of non-linear regression models likelihood functions estimation analysis of deviance checking the model. Part 4 Residuals and…

中位生存时间的估计AI 解读

Two methods are proposed for setting confidence intervals for the median survival time. It is shown how these are related to bootstrap methods for censored data, and some numerical comparisons are presented.

删失数据估计量的影响函数AI 解读

In this paper influence curves for censored data estimators are considered. The influence curve of the Kaplan-Meier estimate of survival time is calculated, and it is shown that the influence curve provides an alternative derivation of the asymptotic variance of this estimate. A chain rule for influence curves is established and is used to calculate the influence curves of censored data estimators that are functions of the Kaplan-Meier estimate. The robustness properties and…

中位生存时间的估计AI 解读

Two methods are proposed for setting confidence intervals for the median survival time. It is shown how these are related to bootstrap methods for censored data, and some numerical comparisons are presented.

K 样本线性秩统计量两种排序方法的渐近等价性AI 解读

Two methods of ranking $K$ samples for rank tests comparing $K$ populations are considered. The first method ranks the $K$ samples jointly; the second ranks the $K$ samples pairwise. These procedures were first suggested by Dunn (1964), and Steel (1960), respectively. It is shown that both ranking procedures are asymptotically equivalent for rank-sum tests satisfying certain nonrestrictive conditions. The problem is formulated in terms of multiple comparisons, but is…