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 …
[HTML][HTML] A novel extension of generalized Rayleigh model with engineering applications
MM Abd El-Raouf, M AbaOud - Alexandria Engineering Journal, 2023 - Elsevier
In this study, we introduce a new flexible distribution constructed by a modification to the
Rayleigh distribution and we referred it as unit generalized Rayleigh distribution (UGRD) …
Rayleigh distribution and we referred it as unit generalized Rayleigh distribution (UGRD) …
Estimation of Entropy for Log‐Logistic Distribution under Progressive Type II Censoring
Entropy is a useful indicator of information content that has been used in a number of
applications. The Log‐Logistic (LL) distribution is a probability distribution that is often …
applications. The Log‐Logistic (LL) distribution is a probability distribution that is often …
[HTML][HTML] Bayesian and non-Bayesian analysis of exponentiated exponential stress–strength model based on generalized progressive hybrid censoring process
In many real-life scenarios, systems frequently perform badly in difficult operating situations.
The multiple failures that take place when systems reach their lower, higher, or extreme …
The multiple failures that take place when systems reach their lower, higher, or extreme …
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 …
Estimation of entropy for inverse Weibull distribution under multiple censored data
Entropy is a measure of uncertainty in a random variable which quantifies the expected
value of the information contained in that random variable. This article estimates the …
value of the information contained in that random variable. This article estimates the …
[HTML][HTML] Estimation of entropy for inverse Lomax distribution under multiple censored data
The inverse Lomax distribution has been widely used in many applied fields such as
reliability, geophysics, economics and engineering sciences. In this paper, an unexplored …
reliability, geophysics, economics and engineering sciences. In this paper, an unexplored …
Product of spacing estimation of entropy for inverse Weibull distribution under progressive type-II censored data with applications
H Okasha, M Nassar - Journal of Taibah University for Science, 2022 - Taylor & Francis
This paper seeks to estimate the entropy for the inverse Weibull distribution using
progressively Type-II censored data. To reach this objective, the entropy is defined through …
progressively Type-II censored data. To reach this objective, the entropy is defined through …
Bayesian Inference for the Entropy of the Rayleigh Model Based on Ordered Ranked Set Sampling
Recently, ranked set samples schemes have become quite popular in reliability analysis
and life-testing problems. Based on ordered ranked set sample, the Bayesian estimators …
and life-testing problems. Based on ordered ranked set sample, the Bayesian estimators …