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Two-step centered spatio-temporal auto-logistic regression model

Abstract : In our study, we focus on spatio-temporal causal auto-logistic model and proposed a two-step-centered parametrization version of it. We study the existence of the joint law according to the conditional marginals. The simulation study show that the one-step model can not reflect the temporal data structure when both spatial and temporal dependance are strong, while for the two-step model, there is an adequate agreement between the data structure and the temporal large-scale structure. The results of estimation for simulated lattices over years were performed by expectation-maximization (EM) pseudo-likelihood in two stages. They show that under the two-step centered parametrization, the inference for parameters of both temporal and spatial regressions are accurate, while under one-step centered parametrization their inference are always conflicting.
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Contributor : Anne Gégout-Petit Connect in order to contact the contributor
Submitted on : Thursday, November 10, 2016 - 9:09:18 AM
Last modification on : Saturday, June 25, 2022 - 7:39:59 PM
Long-term archiving on: : Wednesday, March 15, 2017 - 4:06:45 AM


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  • HAL Id : hal-01394868, version 1



Anne Gégout-Petit, Shuxian Li. Two-step centered spatio-temporal auto-logistic regression model. SADA416, Applied Statistics for Development in Africa, Nov 2016, Cotonou, Benin. ⟨hal-01394868⟩



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