The Logarithmic Burr-Hatke Exponential Distribution for Modeling Reliability and Medical Data

Abouelmagd, T. H. M.

doi:10.5539/ijsp.v7n5p73

Cited by 4 publications

(3 citation statements)

References 19 publications

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“…Both of the two real data sets are available at https://covid19.who.int/. We will examine WBHD in contrast to a variety of well-known models, such as Burr-Hatke distribution (BHD) [22], inverse power Burr-Hatke distribution (IPBHD) [23], logarithmic Burr-Hatke exponential distribution (LBHED) [24], alpha power exponential distribution (APED) [25], Frechet distribution (FD), exponential distribution (ED), Lindley distribution (LND), Lomax distribution (LD),…”

Section: Plos Onementioning

confidence: 99%

Statistical modeling for COVID 19 infected patient’s data in Kingdom of Saudi Arabia

Aldallal

Gemeay²,

Hussam³

et al. 2022

PLoS ONE

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The objective of this study is to construct a new distribution known as the weighted Burr–Hatke distribution (WBHD). The PDF and CDF of the WBHD are derived in a closed form. Moments, incomplete moments, and the quantile function of the proposed distribution are derived mathematically. Eleven estimate techniques for estimating the distribution parameters are discussed, and numerical simulations are utilised to evaluate the various approaches using partial and overall rankings. According to the findings of this study, it is recommended that the maximum product of spacing (MPSE) estimator of the WBHD is the best estimator according to overall rank table. The actuarial measurements were derived to the suggested distribution. By contrasting the WBHD with other competitive distributions using two different actual data sets collected from the COVID-19 mortality rates, we show the importance and flexibility of the WBHD.

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Section: Plos Onementioning

confidence: 99%

Statistical modeling for COVID 19 infected patient’s data in Kingdom of Saudi Arabia

Aldallal

Gemeay²,

Hussam³

et al. 2022

PLoS ONE

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“…Recently, several new distributions and regression models to provide inferences on these distributions have been developed for modeling health and biomedical data, among other fields. Some distributions and classes of distributions developed include exponentiated Burr XII Poisson distribution (da Silva et al [1]), Weibull Burr XII (WBXII) distribution (Afify et al [2]), odd log-logistic Topp-Leone G family of distributions (Alizadeh et al [3]), Burr-Hatke exponential (BHE) distribution (Abouelmagd,[4]; Yadav et al [5]), odd generalized gamma-G family of distributions (Nasir et al [6]), Chen-G family of distributions (Anzagra et al [7]), inverse-power Burr-Hatke distribution (Afify et al [8]), harmonic mixture Weibull-G family of distributions (Zamanah et al [9]), harmonic mixture G family of distributions (Kharazmi et al [10]) and odd log-logistic Weibull-G family of distributions (Rasekhi et al [11]).…”

Section: Introductionmentioning

confidence: 99%

Chen Burr-Hatke Exponential Distribution: Properties, Regressions and Biomedical Applications

Abubakari¹,

Anzagra

Nasiru³

2023

Computational Journal of Mathematical and Statistical Sciences

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Accurately modeling lifetime data is very important for appropriate decision making in health and biomedical fields. This usually requires the use of distributions. However, no single distribution can model all types of data. Hence, the development of distributions with appropriate usefulness is very important for modeling purposes. In this study, a new lifetime distribution, known as Chen Burr-Hatke exponential distribution is proposed. The objective of the study is to obtain a new lifetime distribution which can serve as an alternative distribution to modeling lifetime data. Also, such a distribution can be used to provide inferences via regression models. Plots of the density function of the new distribution show that the distribution can exhibit increasing, decreasing, right-skewed and left-skewed shapes. Also, plots of the hazard rate function show that the distribution can exhibit increasing, decreasing, and upside down bathtub shapes. Statistical properties, such as the quantile function, moments, order statistics and inequality measures, are derived. Several estimation methods are used to estimate the parameters of the distribution. Using Monte Carlo simulations, the estimators were all consistent. However, maximum likelihood estimation method was observed to better estimate the parameters of the distribution. Two regression models based on the distribution are established. The usefulness of the distribution and its regression models are demonstrated using real lifetime datasets. The results show that the models can provide a good fit to lifetime data, and hence can serve as alternative models to fitting such data.

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“…Ref. [11] estimated the BHE model parameter using the maximum likelihood method and considered BHE as an appropriate model for the right-skewed data. Ref.…”

Section: Introductionmentioning

confidence: 99%

Statistical Inference of Burr–Hatke Exponential Distribution with Partially Accelerated Life Test under Progressively Type II Censoring

Gao

Gui

2023

Mathematics

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In this paper, estimations of the parameter and acceleration factor of the Burr–Hatke exponential distribution in partially accelerated life tests under progressively type II censoring are investigated. By using typical maximum likelihood methods and the Bayesian method, point estimations of the distribution parameter and the acceleration factor are obtained. Based on the asymptotic normality and Delta method, approximate confidence intervals are established using the Fisher information matrix. The confidence intervals of the percentile bootstrap method are also evaluated. Comprehensive simulation tests are conducted to evaluate the estimations effects. A real dataset is studied by constructing a Burr–Hatke exponential model and analyzing the practicality and utility of parameter estimation.

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The Logarithmic Burr-Hatke Exponential Distribution for Modeling Reliability and Medical Data

Cited by 4 publications

References 19 publications

Statistical modeling for COVID 19 infected patient’s data in Kingdom of Saudi Arabia

Statistical modeling for COVID 19 infected patient’s data in Kingdom of Saudi Arabia

Chen Burr-Hatke Exponential Distribution: Properties, Regressions and Biomedical Applications

Statistical Inference of Burr–Hatke Exponential Distribution with Partially Accelerated Life Test under Progressively Type II Censoring

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