In this article, we propose a generalization of the modified inverse Weibull distribution. The generalization are motivated by the recent work of Cordeiro et al. [2] and are based on the Kumaraswamy distribution. The generalized distribution is called the Kumaraswamy modified inverse Weibull(KMIW) distribution. We provide a comprehensive description of the structural properties of the subject d...

In this paper, the Kumaraswamy-geometric distribution, which is a member of the T -geometric family of discrete distributions is defined and studied. Some properties of the distribution such as moments, probability generating function, hazard and quantile functions are studied. The method of maximum likelihood estimation is proposed for estimating the model parameters. Two real data sets are us...

The Kumaraswamy distribution is similar to the Beta distribution but has the key advantage of a closed-form cumulative distribution function. In this paper we present the estimation of Kumaraswamy distribution parameters based on Generalized Order Statistics (GOS) using Maximum Likelihood Estimators (MLE). We proved that the parameters estimation for Kumaraswamy distribution can not be obtained...

This article is about twofold arithmetic [1, 2]. Here I introduce algorithms and experimental code for twofold variant of C/C++ standard functions exp() and log(), and expm1() and log1p(). Twofold function y0 + y1 ≈ f(x0 + x1) is nearly 2x-precise so can assess accuracy of standard one. Performance allows assessing on-fly: twofold texp() over double is ~10x times faster than expq() by GNU quadm...

To obtain the SVA objective from the parametric MJP model, we begin by scaling the exponential distribution f(t;λ) = λ exp(−λt), which is an exponential family distribution with natural parameter η = −λ, log-partition function ψ(η) = − ln(−η), and base measure ν(dt) = 1 [1]. To scale the distribution, introduce the new natural parameter η̃ = βη and log-partition function ψ̃(η̃) = βψ(η̃/β). The new ...