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

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Documentation for package ‘nimbleQuad’ version 1.4.0

• DESCRIPTION file
• Package NEWS

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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