Alpha power Maxwell distribution: Properties and application

In this study, alpha power Maxwell (APM) distribution is obtained by applying alpha power transformation, a reparametrized version of the Exp-G family of distributions, to the Maxwell distribution. Some tractable properties of the APM distribution are provided as well. Parameters of the APM distribution are estimated by using the maximum likelihood method. The APM distribution is used to model a real data set and its modeling capability is compared with different distributions, which can be considered its strong alternatives.

[1]  Yuri A. Iriarte,et al.  Gamma-Maxwell distribution , 2017 .

[2]  Dhaifalla K. Al-Mutairi,et al.  Two types of generalized Wiebull distributions and their applications under different enviromental conditions , 1999 .

[3]  B. Şenoğlu,et al.  Slash Maxwell Distribution: Definition, Modified Maximum Likelihood Estimation and Applications , 2020 .

[4]  A. Hassan,et al.  Alpha power transformed extended exponential distribution: properties and applications , 2018, Journal of Nonlinear Sciences and Applications.

[5]  Sanku Dey,et al.  A New Extension of Generalized Exponential Distribution with Application to Ozone Data , 2017 .

[6]  Danna Zhou,et al.  d. , 1840, Microbial pathogenesis.

[7]  Devendra Kumar,et al.  Alpha power transformed inverse Lindley distribution: A distribution with an upside-down bathtub-shaped hazard function , 2019, J. Comput. Appl. Math..

[8]  M. Mesfioui,et al.  A New Extension of Weibull Distribution with Application to Lifetime Data , 2017 .

[9]  A. Bekker,et al.  Reliability Characteristics of the Maxwell Distribution: A Bayes Estimation Study , 2005 .

[10]  W. J. Padgett,et al.  A Bootstrap Control Chart for Weibull Percentiles , 2006, Qual. Reliab. Eng. Int..

[11]  Ayman Alzaatreh,et al.  Methods for generating families of univariate continuous distributions in the recent decades , 2013 .

[12]  M. C. Jones Letter to the Editor concerning “A new method for generating distributions with an application to exponential distribution” and “Alpha power Weibull distribution: Properties and applications” , 2018 .

[13]  On the Bayesian Estimation for two Component Mixture of Maxwell Distribution, Assuming Type I Censored Data , 2012 .

[14]  James Clerk Maxwell,et al.  V. Illustrations of the dynamical theory of gases.—Part I. On the motions and collisions of perfectly elastic spheres , 1860 .

[15]  M. C. Jones,et al.  Log-location-scale-log-concave distributions for survival and reliability analysis , 2015 .

[16]  Z. Hussain,et al.  Parameter and reliability estimation of inverted Maxwell mixture model , 2019, Journal of Statistics and Management Systems.

[17]  Lianfen Qian The Fisher information matrix for a three-parameter exponentiated Weibull distribution under type II censoring , 2011 .

[18]  Ayman Alzaatreh,et al.  Alpha power Weibull distribution: Properties and applications , 2017 .

[19]  James Clerk Maxwell Illustrations of the Dynamical Theory of Gases , 1860 .

[20]  Debasis Kundu,et al.  A new method for generating distributions with an application to exponential distribution , 2017 .

[21]  Robert L. Wolpert,et al.  Statistical Inference , 2019, Encyclopedia of Social Network Analysis and Mining.

[22]  Moshe Shaked,et al.  Stochastic orders and their applications , 1994 .

[23]  Sanku Dey,et al.  Alpha-Power Transformed Lindley Distribution: Properties and Associated Inference with Application to Earthquake Data , 2019 .

[24]  S. Nadarajah,et al.  Truncated-exponential skew-symmetric distributions , 2014 .

[25]  A. B. Simas,et al.  The exp-$G$ family of probability distributions , 2010, 1003.1727.

[26]  Hassan S. Bakouch,et al.  An extended Maxwell distribution: Properties and applications , 2017, Commun. Stat. Simul. Comput..

[27]  Alpha-Power Pareto distribution: Its properties and applications , 2019, PloS one.