Spatial modelling for mixed-state observations
| dc.creator | Hardouin, Cécile | |
| dc.creator | Yao, Jian-Feng | |
| dc.date | 2008-01-15 | |
| dc.date | 2008-03-27 | |
| dc.date.accessioned | 2026-07-07T09:28:36Z | |
| dc.date.available | 2026-07-07T09:28:36Z | |
| dc.description | 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. | |
| dc.description | Published in at http://dx.doi.org/10.1214/08-EJS173 the Electronic Journal of Statistics (http://www.i-journals.org/ejs/) by the Institute of Mathematical Statistics (http://www.imstat.org) | |
| dc.identifier | https://arxiv.org/abs/0801.2231 | |
| dc.identifier | http://arxiv.org/abs/0801.2231 | |
| dc.identifier | Electronic Journal of Statistics 2008, Vol. 2, 213-233 | |
| dc.identifier | doi:10.1214/08-EJS173 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/157481 | |
| dc.subject | Statistics Theory | |
| dc.subject | 62H05, 62E10 (Primary) 62M40 (Secondary) | |
| dc.title | Spatial modelling for mixed-state observations | |
| dc.type | text |