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Bayesian analysis of spatial data using different variance and neighbourhood structures
(Taylor & Francis Ltd, 2016-02-11)
In disease mapping, the overall goal is to study the incidence or mortality risk caused by a specific disease in a number of geographical regions. It is common to assume that the response variable follows a Poisson ...
State space models with spatial deformation
(Environmental and Ecological Statistics, 2013)
A non-homogeneous poisson model with spatial anisotropy applied to ozone data from Mexico City
(Springer, 2015-06-01)
In this work we consider a non-homogenous Poisson model to study the behaviour of the number of times that a pollutant's concentration surpasses a given threshold of interest. Spatial dependence is imposed on the ...
Using a non-homogeneous Poisson model with spatial anisotropy and change-points to study air pollution data
(Springer, 2019-06-01)
A non-homogeneous Poisson process is used to study the rate at which a pollutant's concentration exceeds a given threshold of interest. An anisotropic spatial model is imposed on the parameters of the Poisson intensity ...
Multivariate Spatial IV Regression
(Sociedade Brasileira de Econometria, 2019)
Spatially explicit inference for open populations: Estimating demographic parameters from camera-trap studies
(Ecological Society of America, 2010-11-01)
We develop a hierarchical capture-recapture model for demographically open populations when auxiliary spatial information about location of capture is obtained. Such spatial capture-recapture data arise from studies based ...
A Bayesian Semiparametric Temporally-Stratified Proportional Hazards Model with Spatial Frailties
(INT SOC BAYESIAN ANALYSIS, 2012)
Incorporating temporal and spatial variation could potentially enhance information gathered from survival data. This paper proposes a Bayesian semiparametric model for capturing spatio-temporal heterogeneity within the ...