期刊
FRONTIERS IN APPLIED MATHEMATICS AND STATISTICS
卷 5, 期 -, 页码 -出版社
FRONTIERS MEDIA SA
DOI: 10.3389/fams.2019.00006
关键词
mathematical model; drinking classification; Markov process; stochastic; model fitting; alcohol consumption
资金
- NIH/NIAAA [AA019431]
We simulate a non-human primate's alcohol drinking pattern in order to better understand temporal patterning of alcoholic drinks that can lead to the excessive intakes associated with alcohol use disorder. A stochastic mathematical model of alcohol consumption pattern is developed, where model parameters are calibrated to an individual monkey's drinking history. The model predicts a time series that simulates a monkey's alcohol intake in time, and we analyze this drinking pattern to understand the variations in day and night drinking, the lengths of drinks (intake in 5 or more consecutive secs), and lengths of bouts (1 or more drinks per 5 min occasion). This time series can predict a lifetime categorical drinking level (light, binge, heavy, or very heavy), thus correlating an individual monkey's parameters with distinct long term drinking classifications.
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