613 citations · 2k across the 113 of their papers we have counts for
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stat.ML2015★ 2 cited
Learning the Number of Autoregressive Mixtures in Time Series Using the Gap Statistics
Jie Ding, Mohammad Noshad, Vahid Tarokh
Using a proper model to characterize a time series is crucial in making accurate predictions. In this work we use time-varying autoregressive process (TVAR) to describe non-station…
stat.ML2015★ 1 cited
Data-Driven Learning of the Number of States in Multi-State Autoregressive Models
Jie Ding, Mohammad Noshad, Vahid Tarokh
In this work, we consider the class of multi-state autoregressive processes that can be used to model non-stationary time-series of interest. In order to capture different autoregr…