Laplace Approximation, Quadrature, and Nested Deterministic Approximation Methods for 'nimble'


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Documentation for package ‘nimbleQuad’ version 1.4.0

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AGHQ Laplace approximation and adaptive Gauss-Hermite quadrature
AGHQuad Laplace approximation and adaptive Gauss-Hermite quadrature
approxSummary Main class for nested approximation information
buildAGHQ Laplace approximation and adaptive Gauss-Hermite quadrature
buildLaplace Laplace approximation and adaptive Gauss-Hermite quadrature
buildNestedApprox Build Nested Bayesian Approximation Using Quadrature-based Methods
calcMarginalLogLikImproved Calculate improved marginal log-likelihood using grid-based quadrature
configureQuadGrid Configure Quadrature Grids
dmarginal Evaluate the marginal posterior density for a parameter.
drop_algorithm Drop Algorithm to generate permutations of dimension d with a fixed sum.
emarginal Compute the expectation of a function of a parameter under the marginal posterior distribution
improveParamMarginals Improve univariate parameter marginals using grid-based quadrature
INLA Build Nested Bayesian Approximation Using Quadrature-based Methods
Laplace Laplace approximation and adaptive Gauss-Hermite quadrature
laplace Laplace approximation and adaptive Gauss-Hermite quadrature
logSumExp Log sum exponential.
nested Build Nested Bayesian Approximation Using Quadrature-based Methods
nestedApprox Build Nested Bayesian Approximation Using Quadrature-based Methods
plotMarginal Plot the marginal posterior for a parameter
qmarginal Compute quantiles for a parameter
quadGH Gauss-Hermite Quadrature Points in one dimension
quadGridCache Caching system for building multiple quadrature grids.
quadRule_CCD Central Composite Design (CCD) used for approximate posterior distributions.
quadRule_GH Gauss-Hermite Quadrature Rule for Laplace and Approx Posteriors
QUAD_RULE_BASE Base class for nimble function list quadrature rules.
rmarginal Draw random samples from the marginal posterior of a parameter
runAGHQ Combine steps of running Laplace or adaptive Gauss-Hermite quadrature approximation
runLaplace Combine steps of running Laplace or adaptive Gauss-Hermite quadrature approximation
runNestedApprox Run a nested approximation, returning a summary object with default inference
sampleLatents Sample from the posterior distribution of the latent nodes
sampleParams Sample from the parameter posterior distribution
setParamGrid Set the parameter grid for the nested approximation
summaryAGHQ Summarize results from Laplace or adaptive Gauss-Hermite quadrature approximation
summaryLaplace Summarize results from Laplace or adaptive Gauss-Hermite quadrature approximation