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Title: Random coefficient autoregression on trees Authors:  Anand Vidyashankar - George Mason University (United States) [presenting]
Abstract: Random coefficient autoregression is frequently used to model time series data exhibiting heterogeneity. In applications arising in biology, finance, and insurance, time series models on a random tree are used to obtain predictions. We formalize the concept of general time series models and provide theoretical results concerning predictions that account for both the randomness in the tree and the correlation between the time series and the tree.