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Bayesian Multiple Change-Point for Small Data
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 Title & Authors
Bayesian Multiple Change-Point for Small Data
Cheon, Soo-Young; Yu, Wenxing;
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Bayesian methods have been recently used to identify multiple change-points. However, the studies for small data are limited. This paper suggests the Bayesian noncentral t distribution change-point model for small data, and applies the Metropolis-Hastings-within-Gibbs Sampling algorithm to the proposed model. Numerical results of simulation and real data show the performance of the new model in terms of the quality of the resulting estimation of the numbers and positions of change-points for small data.
Small data;change-point;noncentral t distribution;Metropolis-Hastings-within-Gibbs sampling;Typhoon-frequency;
 Cited by
Bayesian Multiple Change-Point Estimation of Multivariate Mean Vectors for Small Data,;;

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