Approximate Bayesian Inference via Sparse Grid Quadrature Evaluation (BISQuE) for Hierarchical Models

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Documentation for package ‘bisque’ version 1.0.2

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createLocScaleGrid Create a centered and scaled sparse integration grid
dmix Evaluate a mixture density
emix Compute expectations via weighted mixtures
furseals Data from a capture-recapture study of fur seal pups
itx Named inverse transformation functions
jac.exp Jacobian for exponential transform
jac.invlogit Jacobian for logit transform
jac.log Jacobian for log transform
jac.logit Jacobian for logit transform
kCompute Use sparse grid quadrature techniques to integrate (unnormalized) densities
logjac Wrapper to abstractly evaluate log-Jacobian functions for transforms
mergePars Merge pre-computed components of f(theta1 | theta2, X)
sFit Fit a spatially mean-zero spatial Gaussian process model
sKrig Draw posterior predictive samples from a spatial Gaussian process model
tx Named transformation functions
wBuild Derive parameters for building integration grids
wMix Construct a weighted mixture object