Discrete nonhomogeneous and nonstationary logistic and Markov regression models for spatiotemporal data with unresolved external influences

DOI10.2140/CAMCOS.2014.9.1zbMath1314.62010OpenAlexW2151261411MaRDI QIDQ2347618

Illia Horenko, Lars Putzig, Jana de Wiljes

Publication date: 5 June 2015

Published in: Communications in Applied Mathematics and Computational Science (Search for Journal in Brave)

Full work available at URL: https://projecteuclid.org/euclid.camcos/1513732104

zbMATH Keywords

datalogisticnonstationarynonhomogeneoustime-series analysisassimilationMarkov regressiondiscrete spatiotemporal

Mathematics Subject Classification ID

Directional data; spatial statistics (62H11) Inference from stochastic processes and prediction (62M20) Inference from spatial processes (62M30) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Markov processes: estimation; hidden Markov models (62M05) Markov processes: hypothesis testing (62M02) Neural nets and related approaches to inference from stochastic processes (62M45)

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