[LIVRE][B] Bayesian data analysis
Bayesian Data Analysis describes how to conceptualize, perform, and critique statistical
analyses from a Bayesian perspective. Using examples largely from the authors' own …
analyses from a Bayesian perspective. Using examples largely from the authors' own …
Bayesian image restoration, with two applications in spatial statistics
J Besag, J York, A Mollié - Annals of the institute of statistical mathematics, 1991 - Springer
There has been much recent interest in Bayesian image analysis, including such topics as
removal of blur and noise, detection of object boundaries, classification of textures, and …
removal of blur and noise, detection of object boundaries, classification of textures, and …
[LIVRE][B] Gaussian Markov random fields: theory and applications
Gaussian Markov Random Field (GMRF) models are most widely used in spatial statistics-a
very active area of research in which few up-to-date reference works are available. This is …
very active area of research in which few up-to-date reference works are available. This is …
[LIVRE][B] Bayesian disease map**: hierarchical modeling in spatial epidemiology
AB Lawson - 2018 - taylorfrancis.com
Since the publication of the second edition, many new Bayesian tools and methods have
been developed for space-time data analysis, the predictive modeling of health outcomes …
been developed for space-time data analysis, the predictive modeling of health outcomes …
[LIVRE][B] Bayesian biostatistics
E Lesaffre, AB Lawson - 2012 - books.google.com
The growth of biostatistics has been phenomenal in recent years and has been marked by
considerable technical innovation in both methodology and computational practicality. One …
considerable technical innovation in both methodology and computational practicality. One …
On conditional and intrinsic autoregressions
J Besag, C Kooperberg - Biometrika, 1995 - academic.oup.com
Gaussian conditional autoregressions have been widely used in spatial statistics and
Bayesian image analysis, where they are intended to describe interactions between random …
Bayesian image analysis, where they are intended to describe interactions between random …
[LIVRE][B] Statistical methods in spatial epidemiology
AB Lawson - 2013 - books.google.com
Spatial epidemiology is the description and analysis of the geographical distribution of
disease. It is more important now than ever, with modern threats such as bio-terrorism …
disease. It is more important now than ever, with modern threats such as bio-terrorism …
Bayesian computation and stochastic systems
Markov chain Monte Carlo (MCMC) methods have been used extensively in statistical
physics over the last 40 years, in spatial statistics for the past 20 and in Bayesian image …
physics over the last 40 years, in spatial statistics for the past 20 and in Bayesian image …
A close look at the spatial structure implied by the CAR and SAR models
MM Wall - Journal of statistical planning and inference, 2004 - Elsevier
Modeling spatial interactions that arise in spatially referenced data is commonly done by
incorporating the spatial dependence into the covariance structure either explicitly or …
incorporating the spatial dependence into the covariance structure either explicitly or …
[LIVRE][B] Demographic forecasting
Demographic Forecasting introduces new statistical tools that can greatly improve forecasts
of population death rates. Mortality forecasting is used in a wide variety of academic fields …
of population death rates. Mortality forecasting is used in a wide variety of academic fields …