A Hidden Markov Random Field with Copula-Based Emission Distributions for the Analysis of Spatial Cylindrical Data

  • Francesco LagonaEmail author
Conference paper


A hidden Markov random field is proposed for the analysis of spatial cylindrical series. The model is a mixture of copula-based bivariate densities, whose parameters vary across space according to a latent random field. It is exploited to segment coastal currents data within a finite number of latent classes that represent specific environmental conditions.


Cylindrical data Copulas Hidden Markov random fields Marine currents 



F. Lagona was supported by the 2015 PRIN-supported project “Environmental processes and human activities: capturing their interactions via statistical methods,” funded by the Italian Ministry of Education, University and Scientific Research.


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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.University of Roma TreRomeItaly

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