Estimation procedures for a flexible extension of Maxwell distribution with data modeling.

In this paper, we introduce a flexible extension of the Maxwell distribution for modeling various practical data with non-monotone failure rate. Some main properties of this distribution are obtained, and then the estimation of the parameters for the proposed distribution has been addressed by maximum likelihood estimation method and Bayes estimation method. The Bayes estimators have been obtained under gamma prior using squared error loss function. Also, a simulation study is gained to assess the estimates performance. A real-life applications for the proposed distribution have been illustrated through different lifetime data. [ABSTRACT FROM AUTHOR]