The Type II Topp Leone-Power Lomax Distribution with Analysis in Lifetime Data

Aryuyuen, Sirinapa; Bodhisuwan, Winai

doi:10.1007/s42519-020-00091-x

Cited by 3 publications

(1 citation statement)

References 12 publications

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“…Nevertheless, the MLE is the most widely used as baseline method in the framework of various proposed distributions, including the MOPLx distribution. In addition, some newly works on distributions using MLE are illustrated: the Marshall-Olkin Gambel-Lomax distribution (Nwezza & Ugwuowo, 2020), the Marshall-Olkin Exponential Gompertz distribution (Khaleel et al, 2020) and Type II Topp Leone Power Lomax Distribution (Aryuyuen & Bodhisuwan, 2020).…”

Section: Introductionmentioning

confidence: 99%

Parameter estimation methods for the Marshall-Olkin Power Lomax distribution and its applications

Sudsuk¹,

Yamrubboon²

2021

j.appsci

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The Marshall-Olkin Power Lomax (MOPLx) distribution, being extended the Power Lomax distribution, is obtained by using Marshall-Olkin (MO) scheme. This distribution can be applied for skewed data set and used as an alternative to Gamma or Weibull distributions. The main objective of this paper is to compare common method, maximum likelihood estimator (MLE) with the minimum Anderson-Darling estimator (MADE), for the shape and scale parameters of the MOPLx distribution. The efficiency of both estimators for MOPLx distribution is examined via a simulation study with different sample sizes and its specified parameters by using bias, standard deviation and root mean square error as the criteria for the comparison between MLE and MADE. Furthermore, for application of the MOPLx distribution, four life time data sets are exemplified to evaluate the performances of these estimators in both small and large samples.

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Section: Introductionmentioning

confidence: 99%

Parameter estimation methods for the Marshall-Olkin Power Lomax distribution and its applications

Sudsuk¹,

Yamrubboon²

2021

j.appsci

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Bayesian Reliability Analysis of Topp-Leone Model Under Different Loss Functions

Ren¹,

Zhou²,

Yin³

2023

Industrial and Applied Mathematics

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The Markov Bernoulli Lomax with Applications Censored and COVID-19 Drought Mortality Rate Data

Mohammed

Tashkandy

El‐Raouf

et al. 2023

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In this article, we present a Markov Bernoulli Lomax (MB-L) model, which is obtained by a countable mixture of Markov Bernoulli and Lomax distributions, with decreasing and unimodal hazard rate function (HRF). The new model contains Marshall- Olkin Lomax and Lomax distributions as a special case. The mathematical properties, as behavior of probability density function (PDF), HRF, rth moments, moment generating function (MGF) and minimum (maximum) Markov-Bernoulli Geometric (MBG) stable are studied. Moreover, the estimates of the model parameters by maximum likelihood are obtained. The maximum likelihood estimation (MLE), bias and mean squared error (MSE) of MB-L parameters are inspected by simulation study. Finally, a MB-L distribution was fitted to the randomly censored and COVID-19 (complete) data.

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The Type II Topp Leone-Power Lomax Distribution with Analysis in Lifetime Data

Cited by 3 publications

References 12 publications

Parameter estimation methods for the Marshall-Olkin Power Lomax distribution and its applications

Parameter estimation methods for the Marshall-Olkin Power Lomax distribution and its applications

Bayesian Reliability Analysis of Topp-Leone Model Under Different Loss Functions

The Markov Bernoulli Lomax with Applications Censored and COVID-19 Drought Mortality Rate Data

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