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arXiv · 1211.3760

Mixed LICORS: A Nonparametric Algorithm for Predictive State Reconstruction

Georg M. Goerg·Cosma Rohilla Shalizi
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Abstract

We introduce 'mixed LICORS', an algorithm for learning nonlinear, high-dimensional dynamics from spatio-temporal data, suitable for both prediction and simulation. Mixed LICORS extends the recent LICORS algorithm (Goerg and Shalizi, 2012) from hard clustering of predictive distributions to a non-parametric, EM-like soft clustering. This retains the asymptotic predictive optimality of LICORS, but, as we show in simulations, greatly improves out-of-sample forecasts with limited data. The new method is implemented in the publicly-available R package "LICORS" (http://cran.r-project.org/web/packages/LICORS/).

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Georg M. Goerg, Cosma Rohilla Shalizi. 2013-05-03. Mixed LICORS: A Nonparametric Algorithm for Predictive State Reconstruction. https://arxiv.org/abs/1211.3760

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