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

Documentation for package ‘bisque’ version 1.0.2

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