Markov Chain Monte Carlo Small Area Estimation
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Documentation for package ‘mcmcsae’ version 0.7.7
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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_GMRF_matrices | Compute (I)GMRF incidence, precision and restriction matrices corresponding to a generic model component |
| compute_WAIC | Compute DIC, WAIC and leave-one-out cross-validation model measures |
| correlation | Correlation factor structures in generic model components |
| 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 | Functions for specifying a sampling distribution and link function |
| f_gamma | Functions for specifying a sampling distribution and link function |
| f_gaussian | Functions for specifying a sampling distribution and link function |
| f_gaussian_gamma | Functions for specifying a sampling distribution and link function |
| f_multinomial | Functions for specifying a sampling distribution and link function |
| f_negbinomial | Functions for specifying a sampling distribution and link function |
| f_poisson | Functions for specifying a sampling distribution and link function |
-- 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. |
-- 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 | Maximize 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-family | Functions for specifying a sampling distribution and link function |
| mcmcsae_example | Generate artificial data according to an additive spatio-temporal model |
| MCMCsim | Run a Markov Chain Monte Carlo simulation |
| 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 --
| nchains | Get the number of chains, samples per chain or the number of variables in a simulation object |
| nchains-ndraws-nvars | Get the number of chains, samples per chain or the number of variables in a simulation object |
| ndraws | Get the number of chains, samples per chain or the number of variables in a simulation object |
| nvars | Get the number of chains, samples per chain or the number of variables in a simulation object |
| n_eff | Compute MCMC diagnostic measures |
-- 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. |
| 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_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 Generalized Inverse Gaussian (GIG) prior distributions |
| pr_invchisq | Create an object representing inverse chi-squared priors with possibly modeled degrees of freedom and scale parameters |
| pr_invwishart | Create an object representing an inverse Wishart prior, possibly with modeled 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 |
-- 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 |
| spatial | Correlation factor structures in generic model components |
| spline | 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 | Summarize a draws component (dc) object |
| summary.mcdraws | Summarize 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 |