Research Article Open Access

GENERALIZED LINEAR MIXED MODELS WITH SPATIAL RANDOM EFFECTS FOR SPATIO-TEMPORAL DATA: AN APPLICATION TO DENGUE FEVER MAPPING

Krisada Lekdee1 and Lily Ingsrisawang1
  • 1 Kasetsart University, Thailand

Abstract

The Generalized Linear Mixed Models (GLMMs) with spatial random effects for spatio-temporal data are proposed. A hierarchical Bayesian method is used for parameter estimation. The random effects are assumed to be normally distributed and the spatial random effects are assumed to be proper Conditional Autoregressive (CAR) models. The proposed models are applied to Dengue fever data in Northern Thailand, including climatic covariates, rainfall and temperature. The Dengue fever maps are constructed from the posterior mean of the mortality rates.

Journal of Mathematics and Statistics
Volume 9 No. 2, 2013, 137-143

DOI: https://doi.org/10.3844/jmssp.2013.137.143

Submitted On: 22 March 2013 Published On: 13 May 2013

How to Cite: Lekdee, K. & Ingsrisawang, L. (2013). GENERALIZED LINEAR MIXED MODELS WITH SPATIAL RANDOM EFFECTS FOR SPATIO-TEMPORAL DATA: AN APPLICATION TO DENGUE FEVER MAPPING. Journal of Mathematics and Statistics, 9(2), 137-143. https://doi.org/10.3844/jmssp.2013.137.143

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Keywords

  • Generalized Linear Mixed Models
  • Conditional Autoregressive Models
  • Spatial Random Effects Spatio-Temporal Data
  • Dengue Fever Maps