New product reliability prediction has been center of research studies for many years. Reliability prediction focuses on developing a proper reliability model based on available data. Early life reliability prediction is challenging due to the lack of available data thus it is important to use a proper method for reducing this uncertainty. Bayesian method has been used widely in different area ...

The relative excess odds or risk due to interaction (ie, RERIOR and RERI) play an important role in epidemiologic data analysis and interpretation. Previous authors have advocated frequentist approaches based on nonparametric bootstrap, the method of variance estimates recovery, and profile likelihood for estimating confidence intervals. As an alternative, we propose a Bayesian approach that ac...

Use of risk adjusted control charts for monitoring patients’ surgical outcomes is now popular.These charts are developed based on considering the patient’s pre-operation risks. Change point detection is a crucial problem in statistical process control (SPC).It helpsthe managers toanalyzeroot causes of out-of-control conditions more effectively. Since the control chart signals do not necessarily...

We demonstrate the utility of a Bayesian-based approach for calculating intervals of Cronbach’s alpha from a psychological instrument having ordinal responses with a dynamic scale. A small number of response options on an instrument will cause traditional-based interval estimates to be biased. Ordinal-based solutions are problematic because there is no clear mechanism for handling the dynamic s...

A standing question in the field of Intelligent Tutoring Systems and User Modeling in general is what is the appropriate level of model granularity (how many skills to model) and how is that granularity derived? In this paper we will explore varying levels of skill generality within 8 grade mathematics using models containing 1, 5, 39 and 106 skills. We will measure the accuracy of these models...

In spite of the significant work that has been done to discover and recognize activities in the smart home research, less attention has been paid to predict the future activities that the resident is likely to perform. An activity prediction module can play a major role in design of a smart home. For instance, by taking advantage of an activity prediction module, a smart home can learn context-...

The study aims to estimate the parameter of the Generalized Pareto Distribution under Type II censored samples. The Bayes Estimators have been derived under a class of informative and non-informative Priors using different symmetric and asymmetric Loss functions. The Credible Intervals, Highest Posterior Density (HPD) intervals, Posterior Predictive Distributions and Posterior Predictive Interv...