Abstract
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.
| Original language | English (US) |
|---|---|
| Article number | 6 |
| Journal | Frontiers in Applied Mathematics and Statistics |
| Volume | 5 |
| DOIs | |
| State | Published - Feb 22 2019 |
Keywords
- Markov process
- alcohol consumption
- drinking classification
- mathematical model
- model fitting
- stochastic
ASJC Scopus subject areas
- Applied Mathematics
- Statistics and Probability