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Multiple Change-Point Estimation of Air Pollution Mean Vectors
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 Title & Authors
Multiple Change-Point Estimation of Air Pollution Mean Vectors
Kim, Jae-Hee; Cheon, Sooy-Oung;
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The Bayesian multiple change-point estimation has been applied to the daily means of ozone and PM10 data in Seoul for the period 1999. We focus on the detection of multiple change-points in the ozone and PM10 bivariate vectors by evaluating the posterior probabilities and Bayesian information criterion(BIC) using the stochastic approximation Monte Carlo(SAMC) algorithm. The result gives 5 change-points of mean vectors of ozone and PM10, which are related with the seasonal characteristics.
Bayesian change-point model;Bayesian information criterion(BIC);multivariate normal distribution;ozone;PM10;posterior;stochastic approximation Monte Carlo(SAMC);truncated Poisson;
 Cited by
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