R: Adaptive Gauss Hermite Quadrature for Bayesian Inference

# Adaptive Gauss Hermite Quadrature for Bayesian Inference

## Documentation for package ‘aghq’ version 0.4.1

- DESCRIPTION file
- Package NEWS
- Package README

## Help Pages

adaptive_nested_quadrature | Nested, sparse Gaussian quadrature in AGHQ
aghq | Adaptive Gauss-Hermite Quadrature
compute_moment | Compute moments
compute_moment.aghq | Compute moments
compute_moment.default | Compute moments
compute_moment.list | Compute moments
compute_pdf_and_cdf | Density and Cumulative Distribution Function
compute_pdf_and_cdf.aghq | Density and Cumulative Distribution Function
compute_pdf_and_cdf.default | Density and Cumulative Distribution Function
compute_pdf_and_cdf.list | Density and Cumulative Distribution Function
compute_quantiles | Quantiles
compute_quantiles.aghq | Quantiles
compute_quantiles.default | Quantiles
compute_quantiles.list | 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
gcdata | Globular Clusters data for Milky Way mass estimation
gcdatalist | Transformed Globular Clusters data
get_hessian | Obtain the Hessian from an aghq object
get_log_normconst | Obtain the log-normalizing constant from a fitted quadrature object
get_log_normconst.aghq | Obtain the log-normalizing constant from a fitted quadrature object
get_log_normconst.default | Obtain the log-normalizing constant from a fitted quadrature object
get_log_normconst.laplace | Obtain the log-normalizing constant from a fitted quadrature object
get_log_normconst.marginallaplace | Obtain the log-normalizing constant from a fitted quadrature object
get_log_normconst.numeric | 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_nodesandweights.aghq | Obtain the nodes and weights table from a fitted quadrature object
get_nodesandweights.data.frame | Obtain the nodes and weights table from a fitted quadrature object
get_nodesandweights.default | Obtain the nodes and weights table from a fitted quadrature object
get_nodesandweights.laplace | Obtain the nodes and weights table from a fitted quadrature object
get_nodesandweights.list | Obtain the nodes and weights table from a fitted quadrature object
get_nodesandweights.marginallaplace | 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_opt_results.aghq | Obtain the optimization results from an aghq object
get_opt_results.marginallaplace | Obtain the optimization results from an aghq object
get_param_dim | Obtain the parameter dimension from an aghq object
get_param_dim.aghq | Obtain the parameter dimension from an aghq object
get_quadtable | Nested, sparse Gaussian quadrature in AGHQ
get_shift | Compute numeric moments
interpolate_marginal_posterior | Interpolate the Marginal Posterior
laplace_approximation | Laplace Approximation
make_moment_function | Moments of Positive Functions
make_moment_function.aghqmoment | Moments of Positive Functions
make_moment_function.aghqtrans | Moments of Positive Functions
make_moment_function.character | Moments of Positive Functions
make_moment_function.default | Moments of Positive Functions
make_moment_function.function | Moments of Positive Functions
make_moment_function.list | Moments of Positive Functions
make_numeric_moment_function | Compute numeric moments
make_transformation | Marginal Parameter Transformations
make_transformation.aghqtrans | Marginal Parameter Transformations
make_transformation.default | Marginal Parameter Transformations
make_transformation.list | Marginal Parameter Transformations
marginal_laplace | Marginal Laplace approximation
marginal_laplace_tmb | AGHQ-normalized marginal Laplace approximation from a TMB function template
marginal_posterior | Marginal Posteriors
marginal_posterior.aghq | Marginal Posteriors
marginal_posterior.list | Marginal Posteriors
nested_quadrature | 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
sample_marginal.aghq | Exact independent samples from an approximate posterior distribution
sample_marginal.marginallaplace | 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_moment.aghqmoment | Validate a moment function object
validate_moment.character | Validate a moment function object
validate_moment.default | Validate a moment function object
validate_moment.function | Validate a moment function object
validate_moment.list | Validate a moment function object
validate_transformation | Validate a transformation object
validate_transformation.aghqtrans | Validate a transformation object
validate_transformation.default | Validate a transformation object
validate_transformation.list | Validate a transformation object