Rosangela Helena Loschi

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This paper extends previous results for the classical product partition model (PPM) applied to the identification of multiple change points in the means and variances of time series. Prior distributions for these two parameters and for the probability p that a change takes place at a particular period of time are considered and a new scheme based on Gibbs(More)
Classes of shape mixtures of independent and dependent multivariate skew-normal distributions are considered and some of their main properties are studied. If interpreted from a Bayesian point of view, the results obtained in this paper bring tractability to the problem of inference for the shape parameter, that is, the posterior distribution can be written(More)
The well-known product partition model (PPM) is considered for the identi8cation of multiple change points in the means and variances of normal data sequences. In a natural fashion, the PPM may provide product estimates of these parameters at each instant of time, as well as the posterior distributions of the partitions and the number of change points.(More)
One of the greatest challenges related to the use of piecewise exponential models (PEMs) is to find an adequate grid of time-points needed in its construction. In general, the number of intervals in such a grid and the position of their endpoints are ad-hoc choices. We extend previous works by introducing a full Bayesian approach for the piecewise(More)
In this paper the incipient fault detection problem in induction machine stator-winding is considered. The problem is solved using a new technique of change point detection in time series, based on a two-step formulation. The first step consists of a fuzzy clustering to transform the initial data, with arbitrary distribution, into a new one that can be(More)
The multiple change point identification problem may be encountered in many subject areas, including disease mapping, medical diagnosis, industrial control, and finance. One appealing way of tackling the problem is through the product partition model (PPM), a Bayesian approach. Nowadays, practical applications of Bayesian methods have attracted attention(More)
The identification of multiple clusters and/or change points is a problem encountered in many subject areas, ranging from machine learning, pattern recognition, genetics, criminality and disease mapping to finance and industrial control. We present a product partition model that, for the first time, includes dependence between clusters or segments. The(More)
In this paper we analyze the fraction of non-disjunction in Meiosis I assuming reference (non-informative) priors. We consider Jeffreys's approach to built a non-informative prior (Jeffreys's prior) for the fraction of non-disjunction in Meiosis I. We prove that Jeffreys's prior is a proper distribution. We perform Monte Carlo studies in order to compare(More)
Ill-defined causes of death can be related to problems in access to health services or poor quality of medical care and are indicators of data quality in the Mortality Information System (MIS). A sample of municipalities (counties) was selected from the Northeastern Macro-Region of Minas Gerais State, Brazil, with the aim of investigating deaths from(More)