In this article we transmute the half logistic distribution using quadratic rank transmutation map to develop a transmuted half logistic distribution. The quadratic rank transmutation map enables the introduction of extra parameter into its baseline distribution to enhance more flexibility in the analysis of data in various disciplines such as reliability analysis in engineering, survival analysis, medicine, biological sciences, actuarial science, finance and insurance. The mathematical properties such as moments, quantile, mean, median, variance, skewness and kurtosis of this distribution are discussed. The reliability and hazard functions of the transmuted half logistic distribution are obtained. The probability density functions of the minimum and maximum order statistics of the transmuted half logistic distribution are established and the relationships between the probability density functions of the minimum and maximum order statistics of the parent model and the probability density function of the transmuted half logistic distribution are considered. The parameter estimation is done by the method of maximum likelihood estimation. The flexibility of the model in statistical data analysis and its applicability is demonstrated by using it to fit relevant data. The study is concluded by demonstrating that the transmuted half logistic distribution has a better goodness of fit than its parent model. We hope this model will serve as an alternative to the existing ones in the literature in fitting positive real data.
Published in | International Journal of Statistical Distributions and Applications (Volume 5, Issue 3) |
DOI | 10.11648/j.ijsd.20190503.12 |
Page(s) | 54-59 |
Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
Copyright |
Copyright © The Author(s), 2019. Published by Science Publishing Group |
Half Logistic Distribution, Reliability Function, Hazard Rate Function, Parameter Estimation, Order Statistics, Transmutation
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APA Style
Adeyinka Femi Samuel, Olapade Akintayo Kehinde. (2019). A Study on Transmuted Half Logistic Distribution: Properties and Application. International Journal of Statistical Distributions and Applications, 5(3), 54-59. https://doi.org/10.11648/j.ijsd.20190503.12
ACS Style
Adeyinka Femi Samuel; Olapade Akintayo Kehinde. A Study on Transmuted Half Logistic Distribution: Properties and Application. Int. J. Stat. Distrib. Appl. 2019, 5(3), 54-59. doi: 10.11648/j.ijsd.20190503.12
AMA Style
Adeyinka Femi Samuel, Olapade Akintayo Kehinde. A Study on Transmuted Half Logistic Distribution: Properties and Application. Int J Stat Distrib Appl. 2019;5(3):54-59. doi: 10.11648/j.ijsd.20190503.12
@article{10.11648/j.ijsd.20190503.12, author = {Adeyinka Femi Samuel and Olapade Akintayo Kehinde}, title = {A Study on Transmuted Half Logistic Distribution: Properties and Application}, journal = {International Journal of Statistical Distributions and Applications}, volume = {5}, number = {3}, pages = {54-59}, doi = {10.11648/j.ijsd.20190503.12}, url = {https://doi.org/10.11648/j.ijsd.20190503.12}, eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijsd.20190503.12}, abstract = {In this article we transmute the half logistic distribution using quadratic rank transmutation map to develop a transmuted half logistic distribution. The quadratic rank transmutation map enables the introduction of extra parameter into its baseline distribution to enhance more flexibility in the analysis of data in various disciplines such as reliability analysis in engineering, survival analysis, medicine, biological sciences, actuarial science, finance and insurance. The mathematical properties such as moments, quantile, mean, median, variance, skewness and kurtosis of this distribution are discussed. The reliability and hazard functions of the transmuted half logistic distribution are obtained. The probability density functions of the minimum and maximum order statistics of the transmuted half logistic distribution are established and the relationships between the probability density functions of the minimum and maximum order statistics of the parent model and the probability density function of the transmuted half logistic distribution are considered. The parameter estimation is done by the method of maximum likelihood estimation. The flexibility of the model in statistical data analysis and its applicability is demonstrated by using it to fit relevant data. The study is concluded by demonstrating that the transmuted half logistic distribution has a better goodness of fit than its parent model. We hope this model will serve as an alternative to the existing ones in the literature in fitting positive real data.}, year = {2019} }
TY - JOUR T1 - A Study on Transmuted Half Logistic Distribution: Properties and Application AU - Adeyinka Femi Samuel AU - Olapade Akintayo Kehinde Y1 - 2019/08/13 PY - 2019 N1 - https://doi.org/10.11648/j.ijsd.20190503.12 DO - 10.11648/j.ijsd.20190503.12 T2 - International Journal of Statistical Distributions and Applications JF - International Journal of Statistical Distributions and Applications JO - International Journal of Statistical Distributions and Applications SP - 54 EP - 59 PB - Science Publishing Group SN - 2472-3509 UR - https://doi.org/10.11648/j.ijsd.20190503.12 AB - In this article we transmute the half logistic distribution using quadratic rank transmutation map to develop a transmuted half logistic distribution. The quadratic rank transmutation map enables the introduction of extra parameter into its baseline distribution to enhance more flexibility in the analysis of data in various disciplines such as reliability analysis in engineering, survival analysis, medicine, biological sciences, actuarial science, finance and insurance. The mathematical properties such as moments, quantile, mean, median, variance, skewness and kurtosis of this distribution are discussed. The reliability and hazard functions of the transmuted half logistic distribution are obtained. The probability density functions of the minimum and maximum order statistics of the transmuted half logistic distribution are established and the relationships between the probability density functions of the minimum and maximum order statistics of the parent model and the probability density function of the transmuted half logistic distribution are considered. The parameter estimation is done by the method of maximum likelihood estimation. The flexibility of the model in statistical data analysis and its applicability is demonstrated by using it to fit relevant data. The study is concluded by demonstrating that the transmuted half logistic distribution has a better goodness of fit than its parent model. We hope this model will serve as an alternative to the existing ones in the literature in fitting positive real data. VL - 5 IS - 3 ER -