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We express the joint R\'enyi entropy of progressively censored order statistics in terms of an incomplete integral of the hazard function, and provide a simple estimate of the joint R\'enyi entropy of...
In this paper, we introduce a modified test statistic, by applying moving average method and present a new cdf estimator to estimate the joint entropy of the type-II censored data. We also establish a...
Improved EM strategies, based on the idea of efficient data augmentation (Meng and van Dyk 1997, 1998), are presented for ML estimation of mixture proportions. The resulting algorithms inherit the s...
It has been recently shown that nonparametric estimators of the additive regression function could be obtained in the presence of right censoring by coupling the marginal integration method with initi...
In this paper, we propose a new lasso-type estimator for censored data after one-step imputatation. While several penalized likelihood estimators have been proposed for censored data variable selectio...
We obtained estimation results concerning a progressively type-II censored sample from a two-parameter Weibull distribution. The maximum likelihood method is used to derive the point estimators of the...
Diagnostic methods have been an important tool in regression analysis to detect anomalies, such as departures from the error assumptions and the presence of outliers and influential observations with...
It has been recently shown that nonparametric estimators of the additive regression function could be obtained in the presence of right censoring by coupling the marginal integration method with ini...
We develop an active set algorithm for the maximum likelihood estimation of a log–concave density based on complete data. Building on this fast algorithm, we introduce an EM algorithm to treat arbitr...
Higher-order accurate density estimation under random right censorship is achieved using kernel estimators from a family of infinite-order kernels. A compatible bandwidth selection procedure is also...

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