In many practical situations, it is often desired to select a population (treatment, product, technology, etc.) from choice of several populations on the basis particular characteristic that associated with each population, and then estimate selected population. The present paper focused estimating bivariate normal using LINEX loss function. A natural selection rule used for achieving aim selec...

Abstract The article presents a collective risk model for the insurance claims. objective is to estimate premium, which defined as functional specified up unknown parameters. For this purpose, Bayesian methodology, combines prior knowledge about certain parameters with in form of random sample, has been adopted. generalised Bregman loss function considered. In effect, results can be applied num...

In this paper, we focus on the parametric inference based Tampered Random Variable (TRV) model for simple step-stress life testing (SSLT) using Type-II censored data. The baseline lifetime of experimental units, under normal stress conditions, follows Gumbel distribution with $\alpha$ and $\lambda$ being shape scale parameters, respectively. Maximum likelihood estimator (MLE) Bayes parameters a...

This article studies the E-Bayesian estimation of unknown parameter Lomax distribution based on generalized Type-I hybrid censoring. Under square error loss and LINEX functions, we get compare its effectiveness with Bayesian estimation. To measure estimation, expectation mean (E-MSE) is introduced. With Markov chain Monte Carlo technology, estimations are computed. Metropolis–Hastings algorithm...

Abstract: We investigate the derivation of optimal interest rate rules in a simple stochastic framework. The monetary authority chooses to minimise an asymmetric loss function made up of the sum of squared components, where the monetary authority places positive weight on squared negative (positive) deviations of output (inflation) and zero weight on squared positive (negative) deviations. Rece...

Survival data is being analysed here under the middle censoring scheme, using specifically quantile function modelling competing risks. The use of scheme has been shown to be very appropriate COVID-19 pandemic scenario. Cause-specific inference employed. Such inferences are obtained through cumulative incidence based on cause-specific proportional hazards model. baseline lifetime assumed follow...