Progressive Type-II hybrid censored schemes based on maximum product spacing with application to Power Lomax distribution

El-Sherpieny, El-Sayed A.; Almetwally, Ehab M.; Muhammed, Hiba Z.

doi:10.1016/j.physa.2020.124251

Cited by 45 publications

(33 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…e MLE of Θ for the WGED parameters is the solution of equations (15), (16), and (17) by using the Newton-Raphson method. Furthermore, the asymptotic CI (ACI) can be approximated numerically by inverting Fisher's information matrix.…”

Section: Mle Methods Using Equationmentioning

confidence: 99%

“…Also, we propose different bootstrap CIs of population parameters under the MLE method based on ATIIPCS data with binomial removal for the WGED as a bootstrap percentile (BP) and bootstrap-t (BT). For more information about this algorithm, see [31,32] and [15].…”

Section: Mps Methodsmentioning

confidence: 99%

“…Progressive censoring is useful in a life-testing experiment because it has the ability to remove life units from the experiment, so it saves time and money. Applications under progressive Type-II censoring (PTIIC) using different lifetime distributions have been discussed by many authors, for example, see [11][12][13][14]þ and [15].…”

Section: Introductionmentioning

confidence: 99%

“…Basu et al [23] developed MPS estimator for a progressive hybrid Type-I censoring scheme with binomial removals. El-Sherpieny et al [15] introduced progressive Type-II hybrid censoring based on the MPS method with application for power Lomax distribution. Almetwally et al [21] discussed the Weibull parameter estimation under PTIIC by using MPS and MLE methods.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

The Weibull Generalized Exponential Distribution with Censored Sample: Estimation and Application on Real Data

et al. 2021

Self Cite

View full text Add to dashboard Cite

This paper is concerned with the estimation of the Weibull generalized exponential distribution (WGED) parameters based on the adaptive Type-II progressive (ATIIP) censored sample. Maximum likelihood estimation (MLE), maximum product spacing (MPS), and Bayesian estimation based on Markov chain Monte Carlo (MCMC) methods have been determined to find the best estimation method. The Monte Carlo simulation is used to compare the three methods of estimation based on the ATIIP-censored sample, and also, we made a bootstrap confidence interval estimation. We will analyze data related to the distribution about single carbon fiber and electrical data as real data cases to show how the schemes work in practice.

show abstract

Section: Mle Methods Using Equationmentioning

confidence: 99%

Section: Mps Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

The Weibull Generalized Exponential Distribution with Censored Sample: Estimation and Application on Real Data

et al. 2021

Self Cite

View full text Add to dashboard Cite

show abstract

“…It was studied by many authors (Kumar et al, 2017;Mokhlis et al, 2017;Almetwaly and Almongy, 2018;Almetwally et al, 2018;El-Sherpieny et al, 2020). Figure 1 represents the different graphs of pdf of the PL distribution for different values of the parameters.…”

Section: Introductionmentioning

confidence: 99%

Parameter Estimation and Stress-Strength Model of Power Lomax Distribution: Classical Methods and Bayesian Estimation

Almetwally¹,

Almongy²

2021

Journal of Data Science

Self Cite

View full text Add to dashboard Cite

In this paper, parameter estimation for the power Lomax distribution is studied with different methods as maximum likelihood, maximum product spacing, ordinary least squares, weighted least squares, Cramér-von Mises and Bayesian estimation by Markov chain Monte Carlo (MCMC). Robust estimation of the stress-strength model for the Power Lomax distribution is discussed. We propose that the method of maximum product of spacing for reliable estimation of stress-strength model as an alternative method to maximum likelihood and Bayesian estimation methods. A numerical study using real data and Monte Carlo Simulation is performed to compare between different methods.

show abstract

Analysis of Wilson‐Hilferty distribution under progressive Type‐II censoring

Dey¹,

Elshahhat

2022

Quality & Reliability Eng

View full text Add to dashboard Cite

A new re-parameterize form of the Wilson-Hilferty distribution for data modelling with increasing, decreasing and bathtub shape hazard rates has been considered. This paper takes into account the estimation for the unknown model parameters, reliability function and hazard function based on two frequentist methods and Bayesian method of estimation using Type-II progressively censored data. In frequentist method, besides conventional likelihood based estimation, another competitive method, known as maximum product of spacing (MPS) method is proposed to estimate the model parameters, reliability function and hazard function as an alternative approach to the common likelihood method. In Bayesian paradigm, we have also considered the MPS function as an alternative to the traditional likelihood function and both are also discussed under the Bayesian set up for unknown parameters, reliability function and hazard function. Moreover, for all considered unknown quantities, the approximate confidence intervals under the proposed frequentist approaches as well as the Bayes credible intervals are constructed. Extensive Monte-Carlo simulation studies are conducted to evaluate the performance of the proposed estimates with respect to various criteria quantities. Furthermore, we discuss an optimal progressive censoring plan among different competing censoring plans using three optimality criteria. Finally, to show the applicability of the proposed methodologies in a real-life scenario, an engineering dataset is analysed.

show abstract

Progressive Type-II hybrid censored schemes based on maximum product spacing with application to Power Lomax distribution

Cited by 45 publications

References 15 publications

The Weibull Generalized Exponential Distribution with Censored Sample: Estimation and Application on Real Data

The Weibull Generalized Exponential Distribution with Censored Sample: Estimation and Application on Real Data

Parameter Estimation and Stress-Strength Model of Power Lomax Distribution: Classical Methods and Bayesian Estimation

Analysis of Wilson‐Hilferty distribution under progressive Type‐II censoring

Contact Info

Product

Resources

About