background and objective: improved and modified automation will require the development of smart process control systems that provide on-line decisions to release patients’ test results based on high analytical quality assurance formula. materials and methods: we collected patients’ test results from 10840 healthy subjects based on 1.96z as truncation limit for 29 common haematochemical analyte...

abstract profile monitoring in statistical quality control has attracted attention of many researchers recently. a profile is a function between response variables and one or more independent variables. there have been only a limited number of researches on monitoring multivariate profiles. indeed, monitoring correlated multivariate profiles is a new subject in the fileld of statistical process...

The quality of an architectural design of a software system has a great influence on achieving non-functional requirements of a system. A regular software development project is often influenced by non-functional factors such as the customers' expectations about the performance and reliability of the software as well as the reduction of underlying risks. The evaluation of non-functional paramet...

To evaluate the surveillance performance of a control chart with charting statistic sum log likelihood ratios in statistical process (SPC), this paper, we give proof procedure based on Markov chains for asymptotic estimation average run length (ARL) kind chart. The out-of-control ARL 1 </msub...

Presented here are the results of a Metropolis–Hastings Markov chain Monte Carlo routine applied to the problem of determining parameters for coalescing binary systems observed with laser interferometric detectors. The Metropolis– Hastings routine is described in detail, and examples show that signals may be detected and analysed from within noisy data. Using the Bayesian framework of statistic...

The control chart based on geometric distribution (geometric chart) has been shown to be competitive to por npcharts for monitoring proportion nonconforming, especially for applications in high quality manufacturing environment. However, implementing a geometric chart often assumes the process parameter to be known or accurately estimated. For a high quality process, an accurate parameter estim...

This paper presents the use of Bernoulli mixture models for Markov blanket filtering and classification of binary data. Bernoulli mixture models can be seen as a tool for partitioning an n-dimensional hypercube, identifying regions of high data density on the corners of the hypercube. Once Bernoulli mixture models are computed from a training dataset we use them for determining the Markov blank...

A commonly used paradigm in diverse application areas is to assume that an observed set of individual binary features is generated from a Bernoulli distribution with probabilities varying according to a Beta distribution. In this paper, we present our nonparametric variational inference algorithm for the Beta-Bernoulli observation model. Our primary focus is clustering discrete binary data usin...