The Logistic Inverse Lomax Distribution With Properties and Applications

Joshi, Ramesh Kumar; Professor, Trichandra Multiple Campus

doi:10.47191/ijmcr/v9i1.02

Cited by 2 publications

(1 citation statement)

References 4 publications

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“…Chaudhary and Kumar (2021) have also presented the ArcTan Lomax Distribution by taking the Lomax distribution as baseline model. In addition, Joshi and Kumar (2021) used the inverse Lomax distribution as the parent distribution to introduce the Logistic Inverse Lomax distribution. In order to create the Exponentiated Odd Lomax Exponential (EOLE) distribution, Dhungana and Kumar (2022) combined an exponentiated odd function with the Lomax distribution as a baseline distribution.…”

Section: Introductionmentioning

confidence: 99%

Inverse Exponentiated Odd Lomax Exponential Distribution: Properties and Applications

2022

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Background: New family of distributions has important functions in generalization of distributions by modifying some existing distributions for getting more flexible irrespective to applied and practical view point. The Inverse Exponentiated Odd Lomax Exponential Distribution (IEOLE) having four parameters is suggested. Proposed model is based on T-X family of distribution which is the extended form of beta-generated distribution. Based on the LSE, MLE, and CVM methods, the parameters of the proposed distribution are estimated. Different model validation criteria and model comparisons are done by considering other existing models. Materials and methods: IEOLE is compound distribution derived by using theoretical concept of Odd Lomax Exponential distribution and T-X family of distribution. The parameters of the proposed distribution are estimated through the least square, Cramer–Von Mises and maximum likelihood methods. The applicability of the proposed model is evaluated using R programming on two real-life time data sets. Results: The statistical properties and different characteristics like the hazard rate function, the cumulative distribution function, quantile function, skewness, and kurtosis of the proposed model are discussed. Box plots, TTT plot, density fits etc. shows that the proposed model fits better to considered two real data sets. Different model validation criteria such as AIC, BIC, and CAIC are obtained and compared with some existing well-known probability distributions. Conclusion: This study presents new probability model called Inverse Exponentiated Odd Lomax Exponential distribution. The density curves of the model show that it is unimodal having right skewed. The suggested model has proven to be versatile for modeling real-world data due to its increasing-decreasing, right-skewed form. Also, the hazard rate function (HRF) graph is decreasing, decreasing-increasing or inverted bathtub shaped according to the value of the model constants. Different validation criteria show that the suggested model fits data well and the goodness-of-fit shows that proposed model has lesser test statistic value and higher p- value with respect to some existing models.

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Section: Introductionmentioning

confidence: 99%

Inverse Exponentiated Odd Lomax Exponential Distribution: Properties and Applications

2022

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New Lomax-G family of distributions: Statistical properties and applications

Sapkota,

Kumar,

Gemeay

et al. 2023

AIP Advances

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This research article introduces a new family of distributions developed using the innovative beta-generated transformation technique. Among these distributions, the focus is on the inverse exponential power distribution, which exhibits unique reverse-J, inverted bathtub, or monotonically increasing hazard functions. This paper thoroughly investigates the distribution’s key characteristics and utilizes the maximum likelihood estimation method to determine its associated parameters. To assess the accuracy of the estimation procedure, the researchers conducted a simulation experiment, revealing diminishing biases and mean square errors with increasing sample sizes, even when working with small samples. Moreover, the practical applicability of the proposed distribution is demonstrated by analyzing real-world COVID-19 and medical datasets. The article establishes that the proposed model outperforms existing models by using model selection criteria and conducting goodness-of-fit test statistics. The potential applications of this research extend to various fields where modeling and analyzing hazard functions or survival data are crucial. Additionally, the study contributes to advancing probability theory and statistical inferences.

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The Logistic Inverse Lomax Distribution With Properties and Applications

Cited by 2 publications

References 4 publications

Inverse Exponentiated Odd Lomax Exponential Distribution: Properties and Applications

Inverse Exponentiated Odd Lomax Exponential Distribution: Properties and Applications

New Lomax-G family of distributions: Statistical properties and applications

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