We consider a set of independent Bernoulli trials with possibly different success probabilities that depend on covariate values. However, the available data consist only of aggregate numbers of successes among subsets of the trials along with all of the covariate values. We still wish to estimate the parameters of a modeled relationship between the covariates and the success probabilities, e.g....

We propose an efficient and accurate approximate Bayesian Markov chain Monte Carlo methodology for the estimation of event rates under an overdispersed Poisson distribution. A Gibbs sampling algorithm is derived, based on a log-normal/gamma mixture density that closely approximates the conditional distribution of the Poisson parameters. This involves a moment matching process, with the exact co...

This paper proposes a novel data-based approach for estimating the parameters of a stochastic hybrid model describing the traffic flow in an urban traffic network with signalized intersections. The model represents the evolution of the traffic flow rate, measuring the number of vehicles passing a given location per time unit. This traffic flow rate is described in this paper using a mode-depend...

An industrial company requires quality control to maintain consistency from the production results so that it is able compete with other companies in world market. In sector, most processes are influenced by more than one characteristic. One tool can be used characteristic Multivariate Exponentially Weighted Moving Average (MEWMA) chart. The graph determine whether process has been controlled o...

An algorithm is presented that allows the calculation of the probability of a set of sequences related by a binary tree that has evolved according to the Thorne-Kishino-Felsenstein model (1991) for a fixed set of parameters. There are two ideas underlying this algorithm. Firstly, a markov chain is defined that generates ancestral sequences and their alignment at two neighboring nodes in a tree....

there are some problems with estimating the time required for the manufacturing process of products, especially when there is a variable serving time, like control stage. these problems will cause overestimation of process time. layout constraints, reworking constraints and inflexible product schedule in multi product lines need a precise planning to reduce volume in particular situation of lin...

BACKGROUND Time series charts are increasingly used by clinical teams to monitor their performance, but statistical control charts are not widely used, partly due to uncertainty about which chart to use. Although there is a large literature on methods, there are few systematic comparisons of charts for detecting changes in rates of binary clinical performance data. METHODS We compared four co...

In this paper we develop two types of tests to detect changes in the location parameters of dependent observations with infinite variances. We consider the case of autoregressive processes of order one with independent innovations in the domain of attraction of a stable law. If the d largest (in magnitude) observations are removed from the sample, then the standard CUSUM process developed for w...

The Baum-Welch (EM) algorithm is a familiar tool for calculation the maximum likelihood estimate of the parameters in hidden Markov chain models. For the particular case of a binary Markov chain corrupted by binary channel noise a detailed study is carried out of the innuence that the initial conditions impose on the results produced by the algorithm.