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http://dx.doi.org/10.7465/jkdi.2016.27.5.1155

Density estimation of summer extreme temperature over South Korea using mixtures of conditional autoregressive species sampling model  

Jo, Seongil (Department of Statistics and Applied Probability, National University of Singapore)
Lee, Jaeyong (Department of Statistics, Seoul National University)
Publication Information
Journal of the Korean Data and Information Science Society / v.27, no.5, 2016 , pp. 1155-1168 More about this Journal
Abstract
This paper considers a probability density estimation problem of climate values. In particular, we focus on estimating probability densities of summer extreme temperature over South Korea. It is known that the probability density of climate values at one location is similar to those at near by locations and one doesn't follow well known parametric distributions. To accommodate these properties, we use a mixture of conditional autoregressive species sampling model, which is a nonparametric Bayesian model with a spatial dependency. We apply the model to a dataset consisting of summer maximum temperature and minimum temperature over South Korea. The dataset is obtained from University of East Anglia.
Keywords
Conditional autoregressive species sampling model; density estimation; extreme temperature; mercer conditional autoregressive model; spatial correlation;
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Times Cited By KSCI : 3  (Citation Analysis)
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