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Multiple Change-Point Estimation of Air Pollution Mean VectorsMultiple Change-Point Estimation of Air Pollution Mean Vectors
- Other Titles
- Multiple Change-Point Estimation of Air Pollution Mean Vectors
- Issue Date
- 2009
- Publisher
- 한국통계학회
- Keywords
- Bayesian change-point model; Bayesian information criterion(BIC); multivariate normal distribution; ozone; PM10; posterior; stochastic approximation Monte Carlo(SAMC); truncated Poisson.
- Citation
- 응용통계연구, v.22, no.4, pp.687 - 695
- Indexed
- KCI
- Journal Title
- 응용통계연구
- Volume
- 22
- Number
- 4
- Start Page
- 687
- End Page
- 695
- ISSN
- 1225-066X
- 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.
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Collections - Graduate School > Department of Applied Statistics > 1. Journal Articles
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