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http://dx.doi.org/10.5351/CKSS.2007.14.1.001

Forecasting Probability of Precipitation Using Morkov Logistic Regression Model  

Park, Jeong-Soo (Department of Statistics, Chonnam National University)
Kim, Yun-Seon (HR Planning Group, Korea Marketing, LG Electronics Inc.)
Publication Information
Communications for Statistical Applications and Methods / v.14, no.1, 2007 , pp. 1-9 More about this Journal
Abstract
A three-state Markov logistic regression model is suggested to forecast the probability of tomorrow's precipitation based on the current meteorological situation. The suggested model turns out to be better than Markov regression model in the sense of the mean squared error of forecasting for the rainfall data of Seoul area.
Keywords
Binary response; Markov chain; maximum likelihood estimation; mean squared error; rainfall; transition probability;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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