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利用检验功效增强多重决策并控制族错误率与错误发现率AI 解读

Improved procedures, in terms of smaller missed discovery rates (MDR), for performing multiple hypotheses testing with weak and strong control of the family-wise error rate (FWER) or the false discovery rate (FDR) are developed and studied. The improvement over existing procedures such as the Šidák procedure for FWER control and the Benjamini–Hochberg (BH) procedure for FDR control is achieved by exploiting possible differences in the powers of the individual tests. Results…

最小维修模型的次序统计量性质、随机生成与拟合优度检验AI 解读

We present properties of statistics arising from the Block, Borges, and Savits age-dependent minimal repair model. These properties are analogous to the order statistic properties in homogeneous Poisson processes. These properties are exploited to obtain an algorithm for generating a realization from the minimal repair model, and for testing hypothesis concerning the initial distribution function or hazard function of the repair model.

风险率模型复合假设的平滑拟合优度检验AI 解读

Consider a counting process $N(t), t\inT}$ with compensator process ${A(t),t\in T}$, where $A(t)=\int_0^t Y(s) ds, {Y(t), t\in T}$ is an observable predictable process, and $\lambda_0(\dot)$ is an unknown hazard rate function. A general procedure for extending Neyman’s smooth goodness­of­fit test for the composite null hypothesis $H_0: \lambda_0(\dot)\inC ={\lambda_0(\dot;\eta):\eta\in\Gamma\subseteq\Re^q}$ is proposed and developed. The extension is obtained by embedding $C$…

Cox 比例风险模型基准风险的平滑拟合优度检验AI 解读

For the Cox proportional hazards model, the goodness-of-fit problem of testing whether the baseline hazard rate function λ(·) equals some specified hazard rate function λ0(·) in the presence of incomplete data is considered. Extending Neyman's idea, the goodness-of-fit tests are score tests obtained by embedding λ(·) in a larger family of hazard rate functions developed through smooth and possibly random transformations of λ0(·). But whereas their smooth alternatives were…

基于风险率的残差性质及其对模型诊断的影响AI 解读

Model diagnostic procedures in failure time models using hazard-based residuals rely on the assumption that the residual vector closely resembles a random sample from a unit exponential distribution when the model holds. This article formally investigates the validity of this critical assumption by deriving and examining the properties of parametrically, semiparametrically, and nonparametrically estimated residuals for complete and right-censored data. The joint distribution…

随机删失数据的卡方拟合优度检验AI 解读

In this article, procedures analogous to Karl Pearson's well-known chi-squared goodness-of-fit test for a simple null hypothesis are developed under the random censorship model. It is shown that one straightforward analog of Pearson's statistic is diminished in applicability due to the form of its limiting distribution. This leads to the development of an asymptotically exact test based on a Wald-type statistic with a chi-squared limiting null distribution. This test is…

Marshall–Olkin 指数分布的贝叶斯估计AI 解读

SUMMARY Bayes estimators of the parameters of the Marshall–Olkin exponential distribution are obtained when random samples from series and parallel systems are available. The estimators are with respect to the quadratic loss function, and the prior distribution allows for prior dependence among the components of the parameter vector. Exact and approximate highest posterior density credible ellipsoids for the parameters are also obtained. In contrast with series sampling, the…