Precise information of wind speed probability distribution is truly significant for many wind
energy applications. The objective of this study is to evaluate the suitability of different …

We considered the Bayesian analysis of a shape parameter of the Weibull-Exponential
distribution in this paper. We assumed a class of non-informative priors in deriving the …

In this paper, we estimate a shape parameter of the Weibull-Frechet distribution by
considering the Bayesian approach under two non-informative priors using three different …

The Nakagami distribution originated to model the fading of radio signals and is widely used
in various disciplines. In this study, the maximum likelihood (ML) estimation method is used …

In the present paper, a three-parameter Weibull-Lindley distribution is considered for
Bayesian analysis. The estimation of a shape parameter of Weibull-Lindley distribution is …

In this chapter, Erlang distribution is considered. For parameter estimation, maximum
likelihood method of estimation, method of moments and Bayesian method of estimation are …

Estimating the scale parameter of the Gumbel-Lomax Distribution using the Bayesian
method of estimation and evaluating the estimators by assuming two non-informative prior …

Abstract The Weibull-Lomax Distribution has several applications in the areas of sur-vival
analysis, especially where survival chances of an event decrease with time. It has positive …

Wind energy has been the focus of attention by governments over the past several decades
because it is clean and renewable energy source that offers many advantages compared to …

In this work, a new bivariate inverted Nakagami distribution that can be used to model real-
world datasets has been investigated. The newly developed bivariate distribution's …