Change-point problems: A Bayesian nonparametric approach
نویسندگان
چکیده
منابع مشابه
Bayesian Hierarchical Nonparametric Inference for Change-point Problems
SUMMARY Bayesian nonparametric inference for a nonsequential change-point problem is studied. We use a mixture of products of Dirichlet processes as our prior distribution. This allows the data before and after the change-point to be dependent, even when the change point is known. A Gibbs sampler algorithm is also proposed in order to overcome analytic diiculties in computing the posterior dist...
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Change point problems are referred to detect heterogeneity in temporal or spatial data. They have applications in many areas like DNA sequences, financial time series, signal processing, etc. A large number of techniques have been proposed to tackle the problems. One of the most difficult issues is estimating the number of the change points. As in other examples of model selection, the Bayesian...
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ژورنال
عنوان ژورنال: Applications of Mathematics
سال: 1985
ISSN: 0862-7940,1572-9109
DOI: 10.21136/am.1985.104169