A new two-parameter model is proposed using the Kavya–Manoharan (KM) transformation family and Burr X (BX) distribution. The called Kavya–Manoharan–Burr (KMBX) model. statistical properties are obtained, involving quantile (QU) function, moment (MOs), incomplete MOs, conditional MO-generating entropy. Based on simple random sampling (SiRS) ranked set (RaSS), parameters estimated via maximum lik...

The Beta Distribution is almost exclusively used for situations, after range normalization, wherein a continuous random variable is defined on the closed range [0, 1]. Since the beta distribution is intrinsically a two parameter distribution, this creates problems in some applications where specification of more than one parameter is difficult. In this note, two new classes of single parameter ...

In this paper, we estimate the multicomponent stress-strength reliability by assuming the Burr-XII distribution. The research methodology adopted here is to estimate the parameters by using maximum likelihood estimation. The reliability is estimated using the maximum likelihood method of estimation and results are compared using the Monte-Carlo simulation for small samples. By using real data s...

This paper presents the statistical inference on the parameters of the Burr type III distribution, when the data are Type-II hybrid censored. The maximum likelihood estimators are developed for the unknown parameters using the EM algorithm method. We provided the observed Fisher information matrix using the missing information principle which is useful for constructing the asymptotic confidence...

This study is concerned with the problem of estimating reliability function parameters two-parameter Burr XII distribution when data are complete. Concepts such as likelihood estimator, bias, bias ratio, and mean square error defined. The purpose this research investigate properties double-stage shrinkage estimators (DSSEs) obtain equations error, ratio. relative efficiency proposed also invest...