In progressive censoring, items are removed at certain times during the life test. Commonly, it is assumed that the removed items are used for further testing. In order to take into account information about these additional testing in inferential procedures, we propose a two-step model of stage...

This paper aims to analyze the characteristic of wind speed data in Al-Salman site - Iraq using Weibull distribution. Maximum likelihood method (MLM) was used to find out two essential Weibull parameters. The best wind distribution was described by using probability density function and...

As a clean and highly valuable renewable energy, wind energy has gradually become an important branch of energy technology. By means of measurement methods, the wind characteristics, energy applications for distributed wind energy source (DWES) in six sites in Henduan Mountains and economic...

The approximation of G/G/s models from Markov models M/M/s has been studied in the literature. The study of a queue model is detailed in the present article, using times of arrivals and time service distributed by Weibull whose estimation of parameters was performed with the Bayesian method...

I propose a Bayesian method to analyze bid data from first-price auctions under private value paradigms. I use a series representation to specify the valuation density so that bidding monotonicity is always satisfied, and I impose density affiliation by the nonparametric technique of Beresteanu...

We investigate the direct connection between the uncertainty related to estimated stable ratios of stock prices and risk and return of two pairs trading strategies: a conditional statistical arbitrage method and an implicit arbitrage one. A simulation-based Bayesian procedure is introduced for...

The propose of this paper is to develop a Bayesian procedure that adequately account for studies with zero observations in meta-analysis and then we focus the problem in the context of the Bayesian selection models. Also, attention is focused to the link distribution between effectiveness in...

The number of short-time workers from January to April 2020 is used to now- and forecast quarterly GDP growth. We purge the monthly log level series from the systematic component to extract unexpected changes or shocks to log short-time workers. These monthly shocks are included in a univariate...

In this paper, we discuss Bayesian inference of unobserved heterogeneity for unemployment duration data in the presence of right and interval-censoring, and non-proportionality. We employ accelerated failure time models with three different distributional assumptions: log-logistic, log-normal,...

We use the concept of coarsened posteriors to provide robust Bayesian inference via coarsening in order to robustify posteriors arising from stochastic frontier models. These posteriors arise from tempered versions of the likelihood when at most a pre-specified amount of data is used, and are...