Spatio-temporal modelling of dengue fever patterns in peninsular Malaysia from 2015--2017
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Publication:2089373
DOI10.1007/s40840-022-01313-0zbMath1496.62177OpenAlexW4282007387MaRDI QIDQ2089373
Nurul Syafiah Abd Naeeim, Nor Azura Md. Ghani, Nuzlinda Abdul Rahman
Publication date: 6 October 2022
Published in: Bulletin of the Malaysian Mathematical Sciences Society. Second Series (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s40840-022-01313-0
disease mappingspatio-temporal modeldengue diseaseintegrated nested Laplace approximation methodrelative risk estimation
Uses Software
Cites Work
- An Explicit Link between Gaussian Fields and Gaussian Markov Random Fields: The Stochastic Partial Differential Equation Approach
- Disease mapping and spatial regression with count data
- Bayesian image restoration, with two applications in spatial statistics (with discussion)
- Approximate Bayesian Inference for Latent Gaussian models by using Integrated Nested Laplace Approximations
- Estimation in Bayesian Disease Mapping
- Bayesian Measures of Model Complexity and Fit
- Gaussian Markov Random Fields
- Mapping Disease and Mortality Rates Using Empirical Bayes Estimators
- A spatial–temporal study of dengue in Peninsular Malaysia for the year 2017 in two different space–time model
- Relative risk analysis of dengue cases using convolution extended into spatio-temporal model
- Spatial and Spatio‐temporal Bayesian Models with R‐INLA
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