Bayesian factor analysis for spatially correlated data: application to cancer incidence data in Scotland
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Publication:257469
DOI10.1007/s10260-011-0177-9zbMath1333.62020OpenAlexW2157917511MaRDI QIDQ257469
Publication date: 17 March 2016
Published in: Statistical Methods and Applications (Search for Journal in Brave)
Full work available at URL: http://hdl.handle.net/2108/24247
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- Spatial panel data model with error dependence: a Bayesian separable covariance approach
- Models with a Kronecker product covariance structure: estimation and testing
- Bayesian correlated factor analysis of socio-demographic indicators
- Bayesian image restoration, with two applications in spatial statistics (with discussion)
- Bayesian estimation in unrestricted factor analysis: A treatment for Heywood cases
- Modeling and prediction for multivariate spatial factor analysis
- A Bayesian approach to nonlinear latent variable models using the Gibbs sampler and the Metropolis-Hastings algorithm
- Factorization of Separable and Patterned Covariance Matrices for Gibbs Sampling
- Maximum likelihood estimation with missing spatial data and with an application to remotely sensed data
- Bayesian latent variable modelling of multivariate spatio-temporal variation in cancer mortality
- Robustness of bayesian factor analysis estimates
- A Regression Method for Spatial Disease Rates: An Estimating Function Approach
- Hierarchical Spatio-Temporal Mapping of Disease Rates
- Adaptive Rejection Metropolis Sampling within Gibbs Sampling
- On using the sample mean in Bayesian factor analysis
- A comparison of Bayesian spatial models for disease mapping
- Approximate Inference in Generalized Linear Mixed Models
- A Shared Component Model for Detecting Joint and Selective Clustering of Two Diseases
- Jointly Distributed Mean and Mixing Coefficients for Bayesian Source Separation using MCMC and ICM
- Applied Spatial Statistics for Public Health Data
- Hierarchical Models in Environmental Science
- Generalized common spatial factor model
- Bayesian Factor Analysis for Spatially Correlated Data, With Application to Summarizing Area-Level Material Deprivation From Census Data
- VI.—The Estimation of Factor Loadings by the Method of Maximum Likelihood
- Rao's score test in spatial econometrics
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