Improved maximum likelihood estimation of the shape-scale family based on the generalized progressive hybrid censoring scheme
M Maswadah - Journal of Applied Statistics, 2022 - Taylor & Francis
In parametric estimates, the maximum likelihood estimation method is the most popular
method widely used in the social sciences and psychology, although it is biased in situations …
method widely used in the social sciences and psychology, although it is biased in situations …
[HTML][HTML] Estimating the entropy of a Weibull distribution under generalized progressive hybrid censoring
Recently, progressive hybrid censoring schemes have become quite popular in a life-testing
problem and reliability analysis. However, the limitation of the progressive hybrid censoring …
problem and reliability analysis. However, the limitation of the progressive hybrid censoring …
Statistical reliability analysis of electronic devices using generalized progressively hybrid censoring plan
A Elshahhat, WS Abu El Azm - Quality and Reliability …, 2022 - Wiley Online Library
Generalized progressive hybrid censoring plan proposed to overcome the limitation of the
progressive hybrid censoring scheme is that it cannot be applied when very few failures may …
progressive hybrid censoring scheme is that it cannot be applied when very few failures may …
On generalized progressive hybrid censoring in presence of competing risks
The progressive Type-II hybrid censoring scheme introduced by Kundu and Joarder
(Comput Stat Data Anal 50: 2509–2528, 2006), has received some attention in the last few …
(Comput Stat Data Anal 50: 2509–2528, 2006), has received some attention in the last few …
On adaptive progressive hybrid censored Burr type III distribution: application to the nano droplet dispersion data
In the current paper, the maximum likelihood and Bayes estimators for the two shape
parameters of the Burr Type III distribution are investigated based on adaptive Type II …
parameters of the Burr Type III distribution are investigated based on adaptive Type II …
An Optimal Point Estimation Method for the Inverse Weibull Model Parameters Using the Runge-Kutta Method.
M Maswadah - Aligarh Journal of Statistics, 2021 - search.ebscohost.com
In parameter estimation techniques the maximum likelihood estimation method is the most
common technique used in social sciences and psychology although it is usually biased in a …
common technique used in social sciences and psychology although it is usually biased in a …
Classical and Bayesian inference for the Kavya–Manoharan generalized exponential distribution under generalized progressively hybrid censored data
This manuscript focuses on the statistical inference of the Kavya–Manoharan generalized
exponential distribution under the generalized type-I progressive hybrid censoring sample …
exponential distribution under the generalized type-I progressive hybrid censoring sample …
[HTML][HTML] Inference for Weibull competing risks model with partially observed failure causes under generalized progressive hybrid censoring
In this paper, a competing risks model is studied when the latent failure times follow Weibull
distribution. When the failure times are observed under generalized progressive hybrid …
distribution. When the failure times are observed under generalized progressive hybrid …
Exact likelihood inference for exponential distributions under generalized progressive hybrid censoring schemes
Abstract Generalized Type-I and Type-II hybrid censoring schemes as proposed in
Chandrasekar et al.(2004) are extended to progressively Type-II censored data. Using the …
Chandrasekar et al.(2004) are extended to progressively Type-II censored data. Using the …
Inference for partially observed competing risks model for Kumaraswamy distribution under generalized progressive hybrid censoring
In this paper, inference for a competing risks model is studied when latent failure times
follow Kumaraswamy distribution and causes of failure are partially observed. Under …
follow Kumaraswamy distribution and causes of failure are partially observed. Under …