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http://dx.doi.org/10.5351/KJAS.2009.22.4.687

Multiple Change-Point Estimation of Air Pollution Mean Vectors  

Kim, Jae-Hee (Department of Statistics, Duksung Women's University)
Cheon, Sooy-Oung (KU Industry-Academy Cooperation Group Team of Economics and Statistics, Korea University)
Publication Information
The Korean Journal of Applied Statistics / v.22, no.4, 2009 , pp. 687-695 More about this Journal
Abstract
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.
Keywords
Bayesian change-point model; Bayesian information criterion(BIC); multivariate normal distribution; ozone; PM10; posterior; stochastic approximation Monte Carlo(SAMC); truncated Poisson;
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