Manuscript Number : IJSRSET1844338

Spatio-temporal Models Using R-INLA with Generalized Extreme Value Distribution in Hierarchical Bayes Regression

Authors(4) :-Ro'fah Nur Rachmawati, Anik Djuraidah, Anwar Fitrianto, I Made Sumertajaya

Spatio-temporal data containing information about space, time and its interaction allows researchers to describe potential geographical pattern. Bayesian method commonly used in describing spatio-temporal data is simulated based Markov Chain Monte Carlo (MCMC). However, MCMC may be extremely slow in the posterior inference simulation process and it becomes computationally unfeasible if the specified models are complex and designed hierarchically. The Integrated Nested Laplace Approximation (INLA) in R-INLA package is approximated based method and becomes a viable alternative to fundamental limitation of the expensive MCMC computation. This paper aims to model data using Bayes spatial and spatio-temporal models divided in parametric and non-parametric temporal trend specifications. We use the number of poor people as the response that fit to generalized extreme value distribution and investigate the geographical patterns among regions by adding the socioeconomics information data set in Bayes spatial model. In Bayes spatio-temporal models we conclude classical parametric temporal trend as the best model that can describe space-time interaction based on the smallest deviance criteria. All the estimation processes are performed efficiently with R-INLA resulting fast, accurate and guarantee of convergence posterior inferences compared to MCMC's convergence issues.

Authors and Affiliations

Ro'fah Nur Rachmawati
Statistics Department, School of Computer Science, Bina Nusantara University, Jakarta, Indonesia
Anik Djuraidah
Statistics Department, Faculty of Mathematics and Natural Sciences, Bogor Agricultural University, Bogor, Indonesia
Anwar Fitrianto
Statistics Department, Faculty of Mathematics and Natural Sciences, Bogor Agricultural University, Bogor, Indonesia
I Made Sumertajaya
Statistics Department, Faculty of Mathematics and Natural Sciences, Bogor Agricultural University, Bogor, Indonesia

Areal Data, Gaussian Markov Random Field, Laplace Approximation, Random Walk

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Publication Details

Published in : Volume 4 | Issue 4 | March-April 2018
Date of Publication : 2018-04-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 1129-1143
Manuscript Number : IJSRSET1844338
Publisher : Technoscience Academy

Print ISSN : 2395-1990, Online ISSN : 2394-4099

Cite This Article :

Ro'fah Nur Rachmawati, Anik Djuraidah, Anwar Fitrianto, I Made Sumertajaya, " Spatio-temporal Models Using R-INLA with Generalized Extreme Value Distribution in Hierarchical Bayes Regression, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 4, Issue 4, pp.1129-1143, March-April-2018. Journal URL : https://res.ijsrset.com/IJSRSET1844338

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