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In this article, we consider statistical inference based on dependent competing risks data from Marshall-Olkin bivariate Weibull distribution. The maximum likelihood estimates of the unknown model parameters have been computed by using the…

Methodology · Statistics 2023-04-20 Subhankar Dutta , Suchandan Kayal

In this paper, a competing risks model is analyzed based on improved adaptive type-II progressive censored sample (IAT-II PCS). Two independent competing causes of failures are considered. It is assumed that lifetimes of the competing…

Methodology · Statistics 2023-02-20 Subhankar Dutta , Suchandan Kayal

In this article, the analysis of left truncated and right censored competing risks data is carried out, under the assumption of the latent failure times model. It is assumed that there are two competing causes of failures, although most of…

Methodology · Statistics 2020-08-19 Debasis Kundu , Debanjan Mitra , Ayon Ganguly

Kundu and Gupta (2007, Metrika, 65, 159 - 170) provided the analysis of Type-I hybrid censored competing risks data, when the lifetime distribution of the competing causes of failures follow exponential distribution. In this paper we…

Applications · Statistics 2017-07-18 Arnab Koley , D. Kundu , Ayon Ganguly

In this paper we investigate the estimation of the unknown parameters of a competing risk model based on a Weibull distributed decreasing failure rate and an exponentially distributed constant failure rate, under right censored…

Statistics Theory · Mathematics 2021-01-12 Hamida Talhi , Hiba Aiachi , Nadji Rahmania

The analysis of progressively censored data has received considerable attention in the last few years. In this paper we consider the joint progressive censoring scheme for two populations. It is assumed that the lifetime distribution of the…

Methodology · Statistics 2017-06-26 Shuvashree Mondal , Debasis Kundu

Analysis of competing risks data plays an important role in the lifetime data analysis. Recently Feizjavadian and Hashemi (Computational Statistics and Data Analysis, vol. 82, 19-34, 2015) provided a classical inference of a competing risks…

Methodology · Statistics 2021-05-04 Debashis Samanta , Debasis Kundu

In this paper we study bayesian analysis of Modified Weibull distribution under progressively censored competing risk model. This study is made for progressively censored data. We use deterministic scan Gibbs sampling combined with slice…

Computation · Statistics 2016-05-24 Arabin Kumar Dey , Abhilash Jha , Sanku Dey

The progressive Type-II hybrid censoring scheme introduced by Kundu and Joarder (\textit{Computational Statistics and Data Analysis}, 2509-2528, 2006), has received some attention in the last few years. One major drawback of this censoring…

Applications · Statistics 2017-03-06 Arnab Koley , Debasis Kundu

The Type-I and Type-II censoring schemes are the most prominent and commonly used censoring schemes in practice. In this work, a mixture of Type-I and Type- II censoring schemes, named the Type I-Type II mixture censoring scheme, has been…

Methodology · Statistics 2025-07-25 K. K. Anakha , V. M. Chacko

Reliability inference based on parametric distributions is an important problem in electrical and mechanical engineering. Most existing methods rely on approximations or bootstrap procedures, which may not perform satisfactorily when data…

Methodology · Statistics 2026-04-15 Bowen Liu , Malwane M. A. Ananda , Sam Weerahandi

The progressive censoring scheme has received considerable amount of attention in the last fifteen years. During the last few years joint progressive censoring scheme has gained some popularity. Recently, the authors Mondal and Kundu ("A…

Applications · Statistics 2018-01-03 Shuvashree Mondal , Debasis Kundu

There is a substantial literature on testing for the equality of the cumulative incidence functions associated with one specific cause in a competing risks setting across several populations against specific or all alternatives. In this…

Statistics Theory · Mathematics 2008-12-18 Hammou El Barmi , Subhash Kochar , Hari Mukerjee

Interval-censored competing risks data arise when each study subject may experience an event or failure from one of several causes and the failure time is not observed exactly but rather known to lie in an interval between two successive…

Methodology · Statistics 2016-03-02 Lu Mao , D. Y. Lin , Donglin Zeng

In this paper, we consider survival analysis with right-censored data which is a common situation in predictive maintenance and health field. We propose a model based on the estimation of two-parameter Weibull distribution conditionally to…

Methodology · Statistics 2020-02-24 Achraf Bennis , Sandrine Mouysset , Mathieu Serrurier

When data are right-censored, i.e. some outcomes are missing due to a limited period of observation, survival analysis can compute the "time to event". Multiple classes of outcomes lead to a classification variant: predicting the most…

Artificial Intelligence · Computer Science 2024-06-21 Julie Alberge , Vincent Maladière , Olivier Grisel , Judith Abécassis , Gaël Varoquaux

In this paper, we investigate accelerated life testing (ALT) models based on the Weibull distribution with stress-dependent shape and scale parameters. Temperature and voltage are treated as stress variables influencing the lifetime…

Methodology · Statistics 2026-01-13 Rahul Konar , Ramnivas Jat , Neeraj Joshi , Raghu Nandan Sengupta

We present a conformal inference method for constructing lower prediction bounds for survival times from right-censored data, extending recent approaches designed for more restrictive type-I censoring scenarios. The proposed method imputes…

Methodology · Statistics 2025-05-26 Matteo Sesia , Vladimir Svetnik

We investigate the performance of model based bootstrap methods for constructing point-wise confidence intervals around the survival function with interval censored data. We show that bootstrapping from the nonparametric maximum likelihood…

Methodology · Statistics 2013-12-24 Bodhisattva Sen , Gongjun Xu

When dealing with right-censored data, where some outcomes are missing due to a limited observation period, survival analysis -- known as time-to-event analysis -- focuses on predicting the time until an event of interest occurs. Multiple…

Machine Learning · Statistics 2024-10-23 Julie Alberge , Vincent Maladière , Olivier Grisel , Judith Abécassis , Gaël Varoquaux
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