aghq0.4.1 package

Adaptive Gauss Hermite Quadrature for Bayesian Inference

aghq

Adaptive Gauss-Hermite Quadrature

compute_moment

Compute moments

compute_pdf_and_cdf

Density and Cumulative Distribution Function

compute_quantiles

Quantiles

correct_marginals

Correct the posterior marginals of a fitted aghq object

default_control

Default control arguments for aghq::aghq().

default_control_marglaplace

Default control arguments for aghq::marginal_laplace().

default_control_tmb

Default control arguments for aghq::marginal_laplace_tmb().

default_transformation

Default transformation

get_hessian

Obtain the Hessian from an aghq object

get_log_normconst

Obtain the log-normalizing constant from a fitted quadrature object

get_mode

Obtain the mode from an aghq object

get_nodesandweights

Obtain the nodes and weights table from a fitted quadrature object

get_numquadpoints

Obtain the number of quadrature nodes used from an aghq object

get_opt_results

Obtain the optimization results from an aghq object

get_param_dim

Obtain the parameter dimension from an aghq object

interpolate_marginal_posterior

Interpolate the Marginal Posterior

laplace_approximation

Laplace Approximation

make_moment_function

Moments of Positive Functions

make_numeric_moment_function

Compute numeric moments

make_transformation

Marginal Parameter Transformations

marginal_laplace

Marginal Laplace approximation

marginal_laplace_tmb

AGHQ-normalized marginal Laplace approximation from a TMB function tem...

marginal_posterior

Marginal Posteriors

nested

Nested, sparse Gaussian quadrature in AGHQ

normalize_logpost

Normalize the joint posterior using AGHQ

optimize_theta

Obtain function information necessary for performing quadrature

plot.aghq

Plot method for AGHQ objects

print.aghq

Print method for AGHQ objects

print.aghqsummary

Print method for AGHQ summary objects

print.laplace

Print method for AGHQ objects

print.laplacesummary

Print method for laplacesummary objects

print.marginallaplacesummary

Summary statistics for models using marginal Laplace approximations

sample_marginal

Exact independent samples from an approximate posterior distribution

summary.aghq

Summary statistics computed using AGHQ

summary.laplace

Summary method for Laplace Approximation objects

summary.marginallaplace

Summary statistics for models using marginal Laplace approximations

validate_control

Validate a control list

validate_moment

Validate a moment function object

validate_transformation

Validate a transformation object

Adaptive Gauss Hermite Quadrature for Bayesian inference. The AGHQ method for normalizing posterior distributions and making Bayesian inferences based on them. Functions are provided for doing quadrature and marginal Laplace approximations, and summary methods are provided for making inferences based on the results. See Stringer (2021). "Implementing Adaptive Quadrature for Bayesian Inference: the aghq Package" <arXiv:2101.04468>.

  • Maintainer: Alex Stringer
  • License: GPL (>= 3)
  • Last published: 2023-06-02