Infinite Hidden Markov Models for Multiple Multivariate Time Series with Missing Data
含缺失数据的多条多元时间序列无限隐马尔可夫模型
Exposure to air pollution is associated with increased morbidity and mortality. Recent technological advancements permit the collection of time-resolved personal exposure data. Such data are often incomplete with missing observations and exposures below the limit of detection, which limit their use in health effects studies. In this paper we develop an infinite hidden Markov model for multiple asynchronous multivariate time series with missing data. Our model is designed to…