On Estimation of P(Y_1<X<Y_2 ) in Cased Inverse Kumaraswamy Distribution

Abstract

This paper deals with the estimation of the stress strength reliability for a component which has a strength that is independent on opposite lower and upper bound stresses, when the stresses and strength follow Inverse Kumaraswamy Distribution. D estimation approaches were applied, namely the maximum likelihood, moment, and shrinkage methods. Monte Carlo simulation experiments were performed to compare the estimation methods based on the mean squared error criteria.

Using Simulation to Estimate Parameters and Reliability for Alpha Power Rayleigh Distribution

“…The main idea of this method is to equate the population moment to the moment of distribution [5], and that the general formula of the k th moment for (APR) distribution is…”

Estimation of a Parallel Stress-strength Model Based on the Inverse Kumaraswamy Distribution

“…The word 'Reliability' refers to the ability of a system to execute its stated purpose adequately for a specified time under the operational conditions encountered [1]. The stress -strength model is used to compute reliability.…”

Shrinkage estimation of stress strength reliability P (Y❮X❮Z) for lomax distribution based on records

“…Hassan et al (2013) [10] focused on the estimate of R= P[Y < 𝑋 < 𝑍], where Y and Z be a random stress and X be a random strength have Weibull Distribution in presence of k outliers. Hameed et al (2020) [9] focused on the estimate of R= P[Y < 𝑋 < 𝑍], when Y, Z and X are independent and that these stress and strength variable follows Kumaraswamy Distribution. Karam and Ali (2021) [13] discuss the estimation of Stress -Strength Reliability for P[Y<X<Z] using Dagum Distribution.…”