–Thompson sampling is a heuristic algorithm for the multi-armed bandit problem which has long tradition in machine learning. The Bayesian spirit sense that it selects arms based on posterior samples of reward probabilities each arm. By forging connection between combinatorial binary bandits and spike-and-slab variable selection, we propose stochastic optimization approach to subset selection ca...

One mechanism for assisting in various tasks encountered in probabilistic reasoning is to adopt a simple sampling model. A population of interest is first posited, characterized by some random variable, say X . This random variable has a population distribution (often assumed to be normal), characterized by (unknown) parameters. The sampling model posits n independent observations on X , denote...

The general assumption for designing a multivariate control chart is that the multiple variables are independent and normally distributed. This may not be tenable in many practical situations, because with dependency often need to monitored simultaneously ensure process in-control. Gumbel’s Bivariate Exponential (GBE) distribution considered better model skewed data reliability analysis. In thi...

This paper considers an extension of probability space based on interval random variables. In this approach, first, a notion of interval random variable is introduced. Then, based on a family of continuous distribution functions with interval parameters, a concept of probability space of an interval random variable is proposed. Then, the mean and variance of an interval random variable are intr...

Recent studies have shown the X-bar control chart with variable sampling interval detects shifts in the process mean faster than the traditional X-bar chart. These studies are usually based on the assumption that the process data are independently and normally distributed. However, many situations in practice violate these assumptions. In this study, a methodology is developed to economically ...

three k-tree distance and fixed-sized plot designs were used for estimating tree density in sparse oak forests. these forests cover the main part of the zagros mountain area in western iran. they are non-timber-oriented forest but important for protection purposes. the main objective was to investigate the statistical performance of k-tree distance and fixed-sized plot designs in the estimation...