Vol. 9, No. 1, 2014

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ISSN: 2157-5452 (e-only)
ISSN: 1559-3940 (print)
Discrete nonhomogeneous and nonstationary logistic and Markov regression models for spatiotemporal data with unresolved external influences

Jana de Wiljes, Lars Putzig and Illia Horenko

Vol. 9 (2014), No. 1, 1–46
Abstract

Dynamical systems with different characteristic behavior at multiple scales can be modeled with hybrid methods combining a discrete model (e.g., corresponding to the microscale) triggered by a continuous mechanism and vice versa. A data-driven black-box-type framework is proposed, where the discrete model is parametrized with adaptive regression techniques and the output of the continuous counterpart (e.g., output of partial differential equations) is coupled to the discrete system of interest in the form of a fixed exogenous time series of external factors. Data availability represents a significant issue for this type of coupled discrete-continuous model, and it is shown that missing information/observations can be incorporated in the model via a nonstationary and nonhomogeneous formulation. An unbiased estimator for the discrete model dynamics in presence of unobserved external impacts is derived and used to construct a data-based nonstationary and nonhomogeneous parameter estimator based on an appropriately regularized spatiotemporal clustering algorithm. One-step and long-term predictions are considered, and a new Bayesian approach to discrete data assimilation of hidden information is proposed. To illustrate our method, we apply it to synthetic data sets and compare it with standard techniques of the machine-learning community (such as maximum-likelihood estimation, artificial neural networks and support vector machines).

Keywords
nonstationary, nonhomogeneous, discrete spatiotemporal time-series analysis, Markov regression, logistic, data assimilation
Mathematical Subject Classification 2010
Primary: 62-07, 62H30, 62M05, 62M10, 65C60
Secondary: 62M02, 62M20, 62M30, 62M45, 62H11
Milestones
Received: 29 November 2012
Revised: 22 October 2013
Accepted: 15 January 2014
Published: 31 March 2014
Authors
Jana de Wiljes
Institute of Mathematics
Freie Universität Berlin
Arnimallee 6
D-14195 Berlin
Germany
Lars Putzig
Institute of Computational Science
Università della Svizzera Italiana
Via Guiseppe Buffi 13
CH-6900 Lugano
Switzerland
Illia Horenko
Institute of Computational Science
Università della Svizzera Italiana
Via Giuseppe Buffi 13
CH-6904 Lugano
Switzerland