In this paper, we study the transformed Rayleigh Lomax (Trans-RL) distribution which belongs to a certain family of two parameters lifetime distributions given by Wang et al (2010). Confidence intervals and inverse estimators of the Trans-RL parameters are derived in terms of order statistics. A simulation study is conducted to report the coverage probabilities, the average biases and the average relative mean square errors for the maximum likelihood, L-moments and inverse estimators. We compare the performance of these methods under different schemes of progressively Type-II right censoring. Finally, an illustrative example is provided to demonstrate the proposed methods
This paper investigates the statistical inference of inverse power Lomax distribution parameters und...
Abstract. In this paper, the well-known proportional hazards model which includes several well-known...
In this article, we generalize the Inverse Rayleigh distribution using the quadratic rank transmutat...
In this paper, we study the transformed Rayleigh Lomax (Trans-RL) distribution which belongs to a ce...
In this paper, estimation of the parameters of a certain family of two-parameter lifetime distribut...
In this article, estimation of the parameters of a certain family of two-parameter lifetime distribu...
In this paper, estimation of the parameters of a certain family of two-parameter life-time distribut...
In this article, a general family of lifetime distributions is considered under progressive type II ...
Generalizations of univariate distributions are often of interest to serve for real life phenomena. ...
The Power Rayleigh distribution (PRD) is a new extension of the standard one-parameter Rayleigh dist...
The one-parameter Rayleigh model is considered as an underlying model for evaluating the properties ...
We propose and study a two-parameter univariate distribution called the Lomax-Rayleigh distribution,...
Classical statistical analysis of the Rayleigh distribution deals with precise information. However,...
In service (or manufacturing) industries the lifetime performance assessment is important, hence, th...
Censoring is a well known feature recurrent in the analysis of lifetime data, occurring in the model...
This paper investigates the statistical inference of inverse power Lomax distribution parameters und...
Abstract. In this paper, the well-known proportional hazards model which includes several well-known...
In this article, we generalize the Inverse Rayleigh distribution using the quadratic rank transmutat...
In this paper, we study the transformed Rayleigh Lomax (Trans-RL) distribution which belongs to a ce...
In this paper, estimation of the parameters of a certain family of two-parameter lifetime distribut...
In this article, estimation of the parameters of a certain family of two-parameter lifetime distribu...
In this paper, estimation of the parameters of a certain family of two-parameter life-time distribut...
In this article, a general family of lifetime distributions is considered under progressive type II ...
Generalizations of univariate distributions are often of interest to serve for real life phenomena. ...
The Power Rayleigh distribution (PRD) is a new extension of the standard one-parameter Rayleigh dist...
The one-parameter Rayleigh model is considered as an underlying model for evaluating the properties ...
We propose and study a two-parameter univariate distribution called the Lomax-Rayleigh distribution,...
Classical statistical analysis of the Rayleigh distribution deals with precise information. However,...
In service (or manufacturing) industries the lifetime performance assessment is important, hence, th...
Censoring is a well known feature recurrent in the analysis of lifetime data, occurring in the model...
This paper investigates the statistical inference of inverse power Lomax distribution parameters und...
Abstract. In this paper, the well-known proportional hazards model which includes several well-known...
In this article, we generalize the Inverse Rayleigh distribution using the quadratic rank transmutat...