Markov Chain Monte Carlo Small Area Estimation

---

Documentation for package ‘mcmcsae’ version 0.7.9

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

A B C F G I L M N P R S T V W misc

mcmcsae-package

Markov Chain Monte Carlo Small Area Estimation

-- A --

acceptance_rates	Return Metropolis-Hastings acceptance rates
aggrMatrix	Utility function to construct a sparse aggregation matrix from a factor
AR1	Correlation factor structures in generic model components
as.array.dc	Convert a draws component object to another format
as.matrix.dc	Convert a draws component object to another format

-- B --

brt	Create a model component object for a BART (Bayesian Additive Regression Trees) component in the linear predictor

-- C --

CG_control	Set options for the conjugate gradient (CG) sampler
chol_control	Set options for Cholesky decomposition
combine_chains	Combine multiple mcdraws objects into a single one by combining their chains
combine_iters	Combine multiple mcdraws objects into a single one by combining their draws
computeDesignMatrix	Compute a list of design matrices for all terms in a model formula, or based on a sampler environment
compute_DIC	Compute DIC, WAIC and leave-one-out cross-validation model measures
compute_WAIC	Compute DIC, WAIC and leave-one-out cross-validation model measures
correlation	Correlation factor structures in generic model components
create_cMVN_sampler	Set up a function for direct sampling from a constrained multivariate normal distribution
create_sampler	Create a sampler object
create_TMVN_sampler	Set up a sampler object for sampling from a possibly truncated and degenerate multivariate normal distribution
crossprod_mv	Fast matrix-vector multiplications
custom	Correlation factor structures in generic model components

-- F --

fitted.mcdraws	Extract draws of fitted values or residuals from an mcdraws object
f_binomial	Specify a binomial sampling distribution
f_gamma	Specify a Gamma sampling distribution
f_gaussian	Specify a Gaussian sampling distribution
f_gaussian_gamma	Specify a Gaussian-Gamma sampling distribution
f_multinomial	Specify a multinomial sampling distribution
f_negbinomial	Specify a negative binomial sampling distribution
f_poisson	Specify a Poisson sampling distribution

-- G --

gen	Create a model component object for a generic random effects component in the linear predictor
generate_data	Generate a data vector according to a model
gen_control	Set computational options for the sampling algorithms used for a 'gen' model component
get_draw	Extract a list of parameter values for a single draw
get_means	Get means or standard deviations of parameters from the MCMC output in an mcdraws object
get_sds	Get means or standard deviations of parameters from the MCMC output in an mcdraws object
glreg	Create a model object for group-level regression effects within a generic random effects component.
GMRF_structure	Set up a GMRF structure for a generic model component

-- I --

iid	Correlation factor structures in generic model components

-- L --

labels	Get and set the variable labels of a draws component object for a vector-valued parameter
labels.dc	Get and set the variable labels of a draws component object for a vector-valued parameter
labels<-	Get and set the variable labels of a draws component object for a vector-valued parameter
loo.mcdraws	Compute DIC, WAIC and leave-one-out cross-validation model measures

-- M --

matrix-vector	Fast matrix-vector multiplications
maximize_log_lh_p	Maximise the log-likelihood or log-posterior as defined by a sampler closure
MCMC-diagnostics	Compute MCMC diagnostic measures
MCMC-object-conversion	Convert a draws component object to another format
mcmcsae	Markov Chain Monte Carlo Small Area Estimation
mcmcsae_example	Generate artificial data according to an additive spatio-temporal model
MCMCsim	Run a Markov Chain Monte Carlo simulation
mc_offset	Create a model component object for an offset, i.e. fixed, non-parametrised term in the linear predictor
mec	Create a model component object for a regression (fixed effects) component in the linear predictor with measurement errors in quantitative covariates
model-information-criteria	Compute DIC, WAIC and leave-one-out cross-validation model measures
model_matrix	Compute possibly sparse model matrix
m_direct	Functions for specifying the method and corresponding options for sampling from a possibly truncated and degenerate multivariate normal distribution
m_Gibbs	Functions for specifying the method and corresponding options for sampling from a possibly truncated and degenerate multivariate normal distribution
m_HMC	Functions for specifying the method and corresponding options for sampling from a possibly truncated and degenerate multivariate normal distribution
m_HMCZigZag	Functions for specifying the method and corresponding options for sampling from a possibly truncated and degenerate multivariate normal distribution
m_softTMVN	Functions for specifying the method and corresponding options for sampling from a possibly truncated and degenerate multivariate normal distribution

-- N --

negbin_control	Set computational options for the sampling algorithms
n_chains	Get the number of chains, samples per chain or the number of variables in a simulation object
n_chains-n_draws-n_vars	Get the number of chains, samples per chain or the number of variables in a simulation object
n_draws	Get the number of chains, samples per chain or the number of variables in a simulation object
n_eff	Compute MCMC diagnostic measures
n_vars	Get the number of chains, samples per chain or the number of variables in a simulation object

-- P --

par_names	Get the parameter names from an mcdraws object
plot.dc	Trace, density and autocorrelation plots for (parameters of a) draws component (dc) object
plot.mcdraws	Trace, density and autocorrelation plots
plot_coef	Plot a set of model coefficients or predictions with uncertainty intervals based on summaries of simulation results or other objects.
poisson_control	Set computational options for the sampling algorithms
posterior-moments	Get means or standard deviations of parameters from the MCMC output in an mcdraws object
predict.mcdraws	Generate draws from the predictive distribution
print.dc_summary	Display a summary of a 'dc' object
print.mcdraws_summary	Print a summary of MCMC simulation results
pr_beta	Create an object representing beta prior distributions
pr_exp	Create an object representing exponential prior distributions
pr_fixed	Create an object representing a degenerate prior fixing a parameter (vector) to a fixed value
pr_gamma	Create an object representing gamma prior distributions
pr_gig	Create an object representing Generalised Inverse Gaussian (GIG) prior distributions
pr_invchisq	Create an object representing inverse chi-squared priors with possibly modelled degrees of freedom and scale parameters
pr_invwishart	Create an object representing an inverse Wishart prior, possibly with modelled scale matrix
pr_MLiG	Create an object representing a Multivariate Log inverse Gamma (MLiG) prior distribution
pr_normal	Create an object representing a possibly multivariate normal prior distribution
pr_truncnormal	Create an object representing truncated normal prior distributions
pr_unif	Create an object representing uniform prior distributions

-- R --

read_draws	Read MCMC draws from a file
reg	Create a model component object for a regression (fixed effects) component in the linear predictor
residuals-fitted-values	Extract draws of fitted values or residuals from an mcdraws object
residuals.mcdraws	Extract draws of fitted values or residuals from an mcdraws object
RW1	Correlation factor structures in generic model components
RW2	Correlation factor structures in generic model components
R_hat	Compute MCMC diagnostic measures

-- S --

sampler_control	Set computational options for the sampling algorithms
SBC_test	Simulation based calibration
season	Correlation factor structures in generic model components
setup_cluster	Set up a cluster for parallel computing
set_constraints	Set up a system of linear equality and/or inequality constraints
set_MH	Set options for Metropolis-Hastings sampling
sim_marg_var	Compute a Monte Carlo estimate of the marginal variances of a (I)GMRF
spatial	Correlation factor structures in generic model components
splines	Correlation factor structures in generic model components
stop_cluster	Stop a cluster
subset.dc	Select a subset of chains, samples and parameters from a draws component (dc) object
summary.dc	Summarise a draws component (dc) object
summary.mcdraws	Summarise an mcdraws object

-- T --

TMVN-methods	Functions for specifying the method and corresponding options for sampling from a possibly truncated and degenerate multivariate normal distribution
to_draws_array	Convert a draws component object to another format
to_mcmc	Convert a draws component object to another format
transform_dc	Transform one or more draws component objects into a new one by applying a function

-- V --

vfac	Create a model component object for a variance factor component in the variance function of a gaussian sampling distribution
vreg	Create a model component object for a regression component in the variance function of a gaussian sampling distribution

-- W --

waic.mcdraws	Compute DIC, WAIC and leave-one-out cross-validation model measures
weights.mcdraws	Extract weights from an mcdraws object

-- misc --

%m*v%

Fast matrix-vector multiplications