# DISCRIMINATING BETWEEN WEIBULL AND LOG-NORMAL DISTRIBUTIONS BASED ON KULLBACK-LEIBLER DIVERGENCE

@inproceedings{Bromideh2012DISCRIMINATINGBW, title={DISCRIMINATING BETWEEN WEIBULL AND LOG-NORMAL DISTRIBUTIONS BASED ON KULLBACK-LEIBLER DIVERGENCE}, author={Ali Akbar Bromideh}, year={2012} }

The Weibull and Log-Normal distributions are frequently used in reliability to analyze lifetime (or failure time) data. The ratio of maximized likelihood (RML) has been extensively used in choosing between the two distributions. The Kullback-Leibler information is a measure of uncertainty between two densities. We examine the use of Kullback-Leibler Divergence (KLD) in discriminating either the Weibull or Log-Normal distribution. An advantage of the KLD is that it incorporates entropy of each…

## 11 Citations

On Discriminating between Gamma and Log-logistic Distributions in Case of Progressive Type II Censoring

- Computer Science
- 2017

In this paper, the problem of discriminating between gamma and log-logistic distributions is considered in case of progressive type II censoring and the ratio of the maximized likelihood test (RML) is used to discriminate between them.

Model selection among log-normal, Weibull, Gamma and generalized exponential distributions

- Computer ScienceINFOCOM 2017
- 2017

This paper conducts discrimination among four important life distributions — Log-Normal distribution, Weibull distribution, Gamma distribution and Generalized Exponential distribution, and uses three goodness of fit tests, namely, KS test, AIC test and BIC test to choose the best fitting model.

Power Function for the Test For Distinguishing Gamma and Weibull Distribution Families

- Mathematics
- 2019

In other to satisfy his customers, the manufacturer will like to ascertain the lifetime distribution of his products for reliability. Hence, the importance of determining the lifetime distribution of…

Compounded inverse Weibull distributions: Properties, inference and applications

- MathematicsCommun. Stat. Simul. Comput.
- 2019

Two probability distributions are analyzed which are formed by compounding inverse Weibull with zero-truncated Poisson and geometric distributions and are found to exhibit both monotone and non-monotone failure rates.

Discriminating between the Lognormal and Weibull Distributions under Progressive Censoring

- MathematicsCumhuriyet Science Journal
- 2019

Bu calismada, log-normal ve weibull dagilimlari arasinda ayirim icin en cok olabilirlik oran ve Kullback-Leibler uzaklik metotlari tartisilmistir. Calismada, ilerleyen tur sansurlu veri durumu ele…

IMPROVED ESTIMATORS OF BREGMAN DIVERGENCE FOR MODEL SELECTION IN SMALL SAMPLES

- Mathematics
- 2018

Recently in [1, 2], Bromideh introduced the Kullback-Leibler Divergence (KLD) test statistic in discriminating between two models. It was found that the ratio minimized Kullback-Leibler divergence…

A Divergence Measure for STROC Curve in Binary Classification

- Computer Science
- 2014

An ROC model based on truncated distributions is proposed and its importance in classification problems is highlighted and KLD has been estimated using a real data set.

Determination of Appropriate Distribution Functions for the Wind Speed Data Using the R Language

- Environmental Science
- 2019

Accurate determination of the proper distribution and parameters of this distribution according to the wind characteristics of the zone is vital for wind energy investment. In determining a wind…

Gamma ve Weibull Dağılımları Arasında Kullback-Leibler Uzaklığına Dayalı Ayrım

- 2017

Gamma ve Weibull dagilimlari saglik, guvenilirlik, muhendislik vb. ortak uygulama alanlarina sahip olan dagilimlardir. Cogu zaman bu iki dagilim bir veri seti icin benzer sonuc cikarimlar saglasa da…

Strongly Consistent of Kullback-Leibler Divergence Estimator and Tests for Model Selection Based on a Bias Reduced Kernel Density Estimator

- Mathematics
- 2018

In this paper, we study the strong consistency of a bias reduced kernel density estimator and derive a strongly con- sistent Kullback-Leibler divergence (KLD) estimator. As application, we formulate…

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