%0 Journal Article
%T Spatial modelling for mixed-state observations
%A C¨Ścile Hardouin
%A Jian-Feng Yao
%J Mathematics
%D 2008
%I arXiv
%R 10.1214/08-EJS173
%X In several application fields like daily pluviometry data modelling, or motion analysis from image sequences, observations contain two components of different nature. A first part is made with discrete values accounting for some symbolic information and a second part records a continuous (real-valued) measurement. We call such type of observations "mixed-state observations". This paper introduces spatial models suited for the analysis of these kinds of data. We consider multi-parameter auto-models whose local conditional distributions belong to a mixed state exponential family. Specific examples with exponential distributions are detailed, and we present some experimental results for modelling motion measurements from video sequences.
%U http://arxiv.org/abs/0801.2231v2