Fit Multivariate Response Generalized Additive Models using Hamiltonian Monte Carlo

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Documentation for package ‘bayesGAM’ version 0.0.2

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bayesGAM-package The 'bayesGAM' package.
bayesGAM 'bayesGAM' fits a variety of regression models using Hamiltonian Monte Carlo
bayesGAMfit Contains results from 'rstan' as well as the design matrices and other data for the model.
bayesGAMfit-class Contains results from 'rstan' as well as the design matrices and other data for the model.
bloodpressure Blood pressure data from a clinical study
coef-method Extract Model Coefficients
coefficients Extract Model Coefficients
coefficients-method Extract Model Coefficients
create_bivariate_design Creates a design matrix from a bivariate smoothing algorithm
extract_log_lik_bgam Extract the log likelihood from models fit by 'bayesGAM'
extract_log_lik_bgam-method Extract the log likelihood from models fit by 'bayesGAM'
fitted Extract fitted values from a model fit by 'bayesGAM'
fitted-method Extract fitted values from a model fit by 'bayesGAM'
getDesign Design matrices from a 'bayesGAMfit' object
getDesign-method Design matrices from a 'bayesGAMfit' object
getModelSlots Return one or slots from the 'Stan' model in 'bayesGAM'
getModelSlots-method Return one or slots from the 'Stan' model in 'bayesGAM'
getSamples Extract the MCMC samples from an object of type 'bayesGAMfit'
getSamples-method Extract the MCMC samples from an object of type 'bayesGAMfit'
getStanResults Returns the 'stanfit' object generated by 'rstan'
getStanResults-method Returns the 'stanfit' object generated by 'rstan'
L Lag function for autoregressive models
loo_bgam Calls the 'loo' package to perform efficient approximate leave-one-out cross-validation on models fit with 'bayesGAM'
loo_bgam-method Calls the 'loo' package to perform efficient approximate leave-one-out cross-validation on models fit with 'bayesGAM'
loo_compare_bgam Calls the 'loo' package to compare models fit by 'bayesGAMfit'
loo_compare_bgam-method Calls the 'loo' package to compare models fit by 'bayesGAMfit'
mcmc_acf Plotting for MCMC visualization and diagnostics provided by 'bayesplot' package
mcmc_acf-method Plotting for MCMC visualization and diagnostics provided by 'bayesplot' package
mcmc_acf_bar Plotting for MCMC visualization and diagnostics provided by 'bayesplot' package
mcmc_acf_bar-method Plotting for MCMC visualization and diagnostics provided by 'bayesplot' package
mcmc_areas Plotting for MCMC visualization and diagnostics provided by 'bayesplot' package
mcmc_areas-method Plotting for MCMC visualization and diagnostics provided by 'bayesplot' package
mcmc_dens Plotting for MCMC visualization and diagnostics provided by 'bayesplot' package
mcmc_dens-method Plotting for MCMC visualization and diagnostics provided by 'bayesplot' package
mcmc_hex Plotting for MCMC visualization and diagnostics provided by 'bayesplot' package
mcmc_hex-method Plotting for MCMC visualization and diagnostics provided by 'bayesplot' package
mcmc_hist Plotting for MCMC visualization and diagnostics provided by 'bayesplot' package
mcmc_hist-method Plotting for MCMC visualization and diagnostics provided by 'bayesplot' package
mcmc_hist_by_chain Plotting for MCMC visualization and diagnostics provided by 'bayesplot' package
mcmc_hist_by_chain-method Plotting for MCMC visualization and diagnostics provided by 'bayesplot' package
mcmc_intervals Plotting for MCMC visualization and diagnostics provided by 'bayesplot' package
mcmc_intervals-method Plotting for MCMC visualization and diagnostics provided by 'bayesplot' package
mcmc_neff Plotting for MCMC visualization and diagnostics provided by 'bayesplot' package
mcmc_neff-method Plotting for MCMC visualization and diagnostics provided by 'bayesplot' package
mcmc_neff_data Plotting for MCMC visualization and diagnostics provided by 'bayesplot' package
mcmc_neff_data-method Plotting for MCMC visualization and diagnostics provided by 'bayesplot' package
mcmc_neff_hist Plotting for MCMC visualization and diagnostics provided by 'bayesplot' package
mcmc_neff_hist-method Plotting for MCMC visualization and diagnostics provided by 'bayesplot' package
mcmc_pairs Plotting for MCMC visualization and diagnostics provided by 'bayesplot' package
mcmc_pairs-method Plotting for MCMC visualization and diagnostics provided by 'bayesplot' package
mcmc_plots Plotting for MCMC visualization and diagnostics provided by 'bayesplot' package
mcmc_rhat Plotting for MCMC visualization and diagnostics provided by 'bayesplot' package
mcmc_rhat-method Plotting for MCMC visualization and diagnostics provided by 'bayesplot' package
mcmc_rhat_data Plotting for MCMC visualization and diagnostics provided by 'bayesplot' package
mcmc_rhat_data-method Plotting for MCMC visualization and diagnostics provided by 'bayesplot' package
mcmc_rhat_hist Plotting for MCMC visualization and diagnostics provided by 'bayesplot' package
mcmc_rhat_hist-method Plotting for MCMC visualization and diagnostics provided by 'bayesplot' package
mcmc_scatter Plotting for MCMC visualization and diagnostics provided by 'bayesplot' package
mcmc_scatter-method Plotting for MCMC visualization and diagnostics provided by 'bayesplot' package
mcmc_trace Plotting for MCMC visualization and diagnostics provided by 'bayesplot' package
mcmc_trace-method Plotting for MCMC visualization and diagnostics provided by 'bayesplot' package
mcmc_violin Plotting for MCMC visualization and diagnostics provided by 'bayesplot' package
mcmc_violin-method Plotting for MCMC visualization and diagnostics provided by 'bayesplot' package
mvcorrplot Multivariate response correlation plot for 'bayesGAMfit' objects
mvcorrplot-method Multivariate response correlation plot for 'bayesGAMfit' objects
normal Constructor function for Normal priors
np Creates design matrices for univariate and bivariate applications
plot Additional plotting for MCMC visualization and diagnostics.
plot-method Additional plotting for MCMC visualization and diagnostics.
posterior_predict Posterior predictive samples from models fit by 'bayesGAM'
posterior_predict-method Posterior predictive samples from models fit by 'bayesGAM'
ppc_boxplot Plotting for MCMC visualization and diagnostics provided by 'bayesplot' package
ppc_boxplot-method Plotting for MCMC visualization and diagnostics provided by 'bayesplot' package
ppc_dens Plotting for MCMC visualization and diagnostics provided by 'bayesplot' package
ppc_dens-method Plotting for MCMC visualization and diagnostics provided by 'bayesplot' package
ppc_dens_overlay Plotting for MCMC visualization and diagnostics provided by 'bayesplot' package
ppc_dens_overlay-method Plotting for MCMC visualization and diagnostics provided by 'bayesplot' package
ppc_ecdf_overlay Plotting for MCMC visualization and diagnostics provided by 'bayesplot' package
ppc_ecdf_overlay-method Plotting for MCMC visualization and diagnostics provided by 'bayesplot' package
ppc_freqpoly Plotting for MCMC visualization and diagnostics provided by 'bayesplot' package
ppc_freqpoly-method Plotting for MCMC visualization and diagnostics provided by 'bayesplot' package
ppc_hist Plotting for MCMC visualization and diagnostics provided by 'bayesplot' package
ppc_hist-method Plotting for MCMC visualization and diagnostics provided by 'bayesplot' package
ppc_plots Plotting for MCMC visualization and diagnostics provided by 'bayesplot' package
predict Posterior predictive samples from models fit by 'bayesGAM', but with new data
predict-method Posterior predictive samples from models fit by 'bayesGAM', but with new data
reef Coral reef data from survey data on 6 sites
show-method Contains results from 'rstan' as well as the design matrices and other data for the model.
showPrior Display the priors used in 'bayesGAM'
showPrior-method Display the priors used in 'bayesGAM'
st Constructor function for Student-t priors
summary Summarizing Model Fits from 'bayesGAM'
summary-method Summarizing Model Fits from 'bayesGAM'
waic_bgam Calls the 'loo' package to calculate the widely applicable information criterion (WAIC)
waic_bgam-method Calls the 'loo' package to calculate the widely applicable information criterion (WAIC)