Kernel and CDF-Based Estimation of Extropy and Entropy from Progressively Type-II Censoring with Application for Goodness of Fit Problems

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Rajaa Hazeb ◽  
Husam A. Bayoud ◽  
Mohammad Z. Raqab
Keyword(s):  
Uniform Distribution ◽  
Goodness Of Fit ◽  
Type Ii ◽  
Type Ii Censoring ◽  
Goodness Of Fit Tests ◽  
Progressive Type ◽  
And Behavior ◽  
Progressive Type Ii Censoring

Abstract Recently, entropy and extropy-based tests for the uniform distribution have attracted the attention of some researchers. This paper proposes nonparametric entropy and extropy estimators based on progressive type-II censoring and investigates their properties and behavior. Performance of the proposed estimators is studied via simulations. Entropy and extropy-based goodness-of-fit tests for uniformity are developed by the well performed estimators. The powers of the proposed uniformity tests are compared also via simulations assuming various alternatives and censoring schemes.

scholarly journals Goodness of Fit Tests for the Log-Logistic Distribution Based on Cumulative Entropy under Progressive Type II Censoring

Mathematics ◽  
2019 ◽  
Vol 7 (4) ◽  
pp. 361 ◽  
Author(s):  
Yuge Du ◽  
Wenhao Gui
Keyword(s):  
Goodness Of Fit ◽  
Likelihood Estimation ◽  
Logistic Distribution ◽  
Type Ii ◽  
Type Ii Censoring ◽  
Goodness Of Fit Tests ◽  
Progressive Type ◽  
Leibler Information ◽  
Cumulative Residual ◽  
Progressive Type Ii Censoring

In this paper, we propose two new methods to perform goodness-of-fit tests on the log-logistic distribution under progressive Type II censoring based on the cumulative residual Kullback-Leibler information and cumulative Kullback-Leibler information. Maximum likelihood estimation and the EM algorithm are used for statistical inference of the unknown parameter. The Monte Carlo simulation is conducted to study the power analysis on the alternative distributions of the hazard function monotonically increasing and decreasing. Finally, we present illustrative examples to show the applicability of the proposed methods.

scholarly journals New Approach for a Weibull Distribution under the Progressive Type-II Censoring Scheme

Mathematics ◽  
2020 ◽  
Vol 8 (10) ◽  
pp. 1713
Author(s):  
Jung-In Seo ◽  
Young Eun Jeon ◽  
Suk-Bok Kang
Keyword(s):  
Weibull Distribution ◽  
Goodness Of Fit ◽  
Type Ii ◽  
Pivotal Quantity ◽  
Rounding Errors ◽  
New Approach ◽  
Type Ii Censoring ◽  
Progressive Type ◽  
Censoring Scheme ◽  
Progressive Type Ii Censoring

This paper proposes a new approach based on the regression framework employing a pivotal quantity to estimate unknown parameters of a Weibull distribution under the progressive Type-II censoring scheme, which provides a closed form solution for the shape parameter, unlike its maximum likelihood estimator counterpart. To resolve serious rounding errors for the exact mean and variance of the pivotal quantity, two different types of Taylor series expansion are applied, and the resulting performance is enhanced in terms of the mean square error and bias obtained through the Monte Carlo simulation. Finally, an actual application example, including a simple goodness-of-fit analysis of the actual test data based on the pivotal quantity, proves the feasibility and applicability of the proposed approach.

On estimation ofR=P(Y

2012 ◽  
Vol 82 (5) ◽  
pp. 729-744 ◽  
Author(s):  
Buğra Saraçoğlu ◽  
Ismail Kinaci ◽  
Debasis Kundu
Keyword(s):  
Exponential Distribution ◽  
Type Ii ◽  
Type Ii Censoring ◽  
Progressive Type ◽  
Progressive Type Ii Censoring

Estimation for flexible Weibull extension under progressive Type-II censoring

2021 ◽  
Vol 13 (1) ◽  
pp. 21-42
Author(s):  
Sanjay Kumar Singh ◽  
Umesh Singh ◽  
Vikas Kumar Sharma ◽  
Manoj Kumar
Keyword(s):  
Type Ii ◽  
Type Ii Censoring ◽  
Progressive Type ◽  
Progressive Type Ii Censoring

scholarly journals Estimations of Weibull-Geometric Distribution under Progressive Type II Censoring Samples

2015 ◽  
Vol 05 (07) ◽  
pp. 721-729 ◽  
Author(s):  
Azhari A. Elhag ◽  
Omar I. O. Ibrahim ◽  
Mohamed A. El-Sayed ◽  
Gamal A. Abd-Elmougod
Keyword(s):  
Geometric Distribution ◽  
Type Ii ◽  
Type Ii Censoring ◽  
Progressive Type ◽  
Progressive Type Ii Censoring
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