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利用单调多项式样条估计面板计数数据的均值函数AI 解读

We study nonparametric likelihood-based estimators of the mean function of counting processes with panel count data using monotone polynomial splines. The generalized Rosen algorithm, proposed by Zhang & Jamshidian (2004), is used to compute the estimators. We show that the proposed spline likelihood-based estimators are consistent and that their rate of convergence can be faster than n-super-1/3. Simulation studies with moderate samples show that the estimators have smaller…

面板计数数据的半参数伪似然估计方法AI 解读

In this paper, we study panel count data with covariates. A semiparametric pseudolikelihood estimation method is proposed based on the assumption that, given a covariate vector Z, the underlying counting process is a nonhomogeneous Poisson process with the conditional mean function given by E{N (t) |Z} = Λ0 (t) exp (β′0Z). The proposed estimation method is shown to be robust in the sense that the estimator converges to its true value regardless of whether or not N (t) is a…

第二类区间删失下失效函数的非参数两样本检验AI 解读

For the setting of interval censoring case 2, a nonparametric two‐sample test, based on a smooth functional of the nonparametric maximum pseudolikelihood estimator, is developed to compare the failure functions of two populations. Monte Carlo simulation studies on Weibull distributions show that this test performs quite well in many situations in comparison with the parametric likelihood ratio test. A real dataset from an study is used to illustrate the new test.