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Estimation and prediction for spatial generalized linear mixed models with parametric links via reparameterized importance sampling
Spatial generalized linear mixed models (SGLMMs) are popular for analyzing non-Gaussian spatial data. These models assume a prescribed link function that relates the underlying spatial field with the mean response. There are...
Geostatistics Laplace approximation Markov Chain Monte Carlo model selection Multiple importance sampling Reverse logistic regression /dk/atira/pure/subjectarea/asjc/2600/2613 name=Statistics and Probability /dk/atira/pure/subjectarea/asjc/1900/1903 name=Computers in Earth Sciences /dk/atira/pure/subjectarea/asjc/2300/2308 name=Management, Monitoring, Policy and Law
Estimation and prediction for spatial generalized linear mixed models using high order Laplace approximation
Estimation and prediction in generalized linear mixed models are often hampered by intractable high dimensional integrals. This paper provides a framework to solve this intractability, using asymptotic expansions when the number...
The value of information for correlated GLMs
We examine the situation where a decision maker is considering investing in a number of projects with uncertain revenues. Before making a decision, the investor has the option to purchase data which carry information about the...
Estimation and prediction for spatial generalized linear mixed models with parametric links via reparameterized importance sampling
Spatial generalized linear mixed models (SGLMMs) are popular for analyzing non-Gaussian spatial data. These models assume a prescribed link function that relates the underlying spatial field with the mean response. There are...
Geostatistics Laplace approximation Markov Chain Monte Carlo model selection Multiple importance sampling Reverse logistic regression /dk/atira/pure/subjectarea/asjc/2600/2613 name=Statistics and Probability /dk/atira/pure/subjectarea/asjc/1900/1903 name=Computers in Earth Sciences /dk/atira/pure/subjectarea/asjc/2300/2308 name=Management, Monitoring, Policy and Law
Estimation and prediction for spatial generalized linear mixed models using high order Laplace approximation
Estimation and prediction in generalized linear mixed models are often hampered by intractable high dimensional integrals. This paper provides a framework to solve this intractability, using asymptotic expansions when the number...
The value of information for correlated GLMs
We examine the situation where a decision maker is considering investing in a number of projects with uncertain revenues. Before making a decision, the investor has the option to purchase data which carry information about the...