A B C D E F G H I L M N P R S T U V misc
| add_residuals | Calculate randomized quantile residuals for mvgam objects |
| add_residuals.mvgam | Calculate randomized quantile residuals for mvgam objects |
| all_neon_tick_data | NEON Amblyomma and Ixodes tick abundance survey data |
| and | Index 'mvgam' objects |
| AR | Specify autoregressive dynamic processes |
| as.array.mvgam | Extract posterior draws from fitted 'mvgam' objects |
| as.data.frame.mvgam | Extract posterior draws from fitted 'mvgam' objects |
| as.matrix.mvgam | Extract posterior draws from fitted 'mvgam' objects |
| as_draws.mvgam | Extract posterior draws from fitted 'mvgam' objects |
| as_draws_array.mvgam | Extract posterior draws from fitted 'mvgam' objects |
| as_draws_df.mvgam | Extract posterior draws from fitted 'mvgam' objects |
| as_draws_list.mvgam | Extract posterior draws from fitted 'mvgam' objects |
| as_draws_matrix.mvgam | Extract posterior draws from fitted 'mvgam' objects |
| as_draws_rvars.mvgam | Extract posterior draws from fitted 'mvgam' objects |
| bernoulli | Supported mvgam families |
| betar | Supported mvgam families |
| beta_binomial | Supported mvgam families |
| CAR | Specify autoregressive dynamic processes |
| code | Stan code and data objects for mvgam models |
| coef.mvgam | Summary for a fitted mvgam object |
| coefficient | Index 'mvgam' objects |
| compare_mvgams | Evaluate forecasts from fitted mvgam objects |
| conditional_effects.mvgam | Display Conditional Effects of Predictors |
| draw.mvgam | Enhance mvgam post-processing using gratia functionality |
| drawDotmvgam | Enhance mvgam post-processing using gratia functionality |
| dynamic | Defining dynamic coefficients in mvgam formulae |
| ensemble | Combine mvgam forecasts into evenly weighted ensembles |
| ensemble.mvgam_forecast | Combine mvgam forecasts into evenly weighted ensembles |
| evaluate_mvgams | Evaluate forecasts from fitted mvgam objects |
| eval_mvgam | Evaluate forecasts from fitted mvgam objects |
| eval_smooth.hilbert.smooth | Enhance mvgam post-processing using gratia functionality |
| eval_smooth.mod.smooth | Enhance mvgam post-processing using gratia functionality |
| eval_smooth.moi.smooth | Enhance mvgam post-processing using gratia functionality |
| eval_smoothDothilbertDotsmooth | Enhance mvgam post-processing using gratia functionality |
| eval_smoothDotmodDotsmooth | Enhance mvgam post-processing using gratia functionality |
| eval_smoothDotmoiDotsmooth | Enhance mvgam post-processing using gratia functionality |
| find_predictors.mvgam | Helper functions for mvgam marginaleffects calculations |
| find_predictors.mvgam_prefit | Helper functions for mvgam marginaleffects calculations |
| fitted.mvgam | Expected Values of the Posterior Predictive Distribution |
| forecast | Extract or compute hindcasts and forecasts for a fitted 'mvgam' object |
| forecast.mvgam | Extract or compute hindcasts and forecasts for a fitted 'mvgam' object |
| formula.mvgam | Extract formulae from mvgam objects |
| formula.mvgam_prefit | Extract formulae from mvgam objects |
| get_coef.mvgam | Helper functions for mvgam marginaleffects calculations |
| get_data.mvgam | Helper functions for mvgam marginaleffects calculations |
| get_data.mvgam_prefit | Helper functions for mvgam marginaleffects calculations |
| get_mvgam_priors | Extract information on default prior distributions for an mvgam model |
| get_predict.mvgam | Helper functions for mvgam marginaleffects calculations |
| get_vcov.mvgam | Helper functions for mvgam marginaleffects calculations |
| GP | Specify dynamic Gaussian processes |
| gratia_mvgam_enhancements | Enhance mvgam post-processing using gratia functionality |
| hindcast | Extract hindcasts for a fitted 'mvgam' object |
| hindcast.mvgam | Extract hindcasts for a fitted 'mvgam' object |
| Index | Index 'mvgam' objects |
| index-mvgam | Index 'mvgam' objects |
| irf | Calculate latent VAR impulse response functions |
| irf.mvgam | Calculate latent VAR impulse response functions |
| lfo_cv | Approximate leave-future-out cross-validation of fitted 'mvgam' objects |
| lfo_cv.mvgam | Approximate leave-future-out cross-validation of fitted 'mvgam' objects |
| logLik.mvgam | Compute pointwise Log-Likelihoods from fitted 'mvgam' objects |
| lognormal | Supported mvgam families |
| log_posterior.mvgam | Extract diagnostic quantities of 'mvgam' models |
| loo.mvgam | LOO information criteria for 'mvgam' models |
| loo_compare.mvgam | LOO information criteria for 'mvgam' models |
| lv_correlations | Calculate trend correlations based on mvgam latent factor loadings |
| mcmc_plot.mvgam | MCMC plots as implemented in 'bayesplot' |
| model.frame.mvgam | Extract model.frame from a fitted mvgam object |
| model.frame.mvgam_prefit | Extract model.frame from a fitted mvgam object |
| monotonic | Monotonic splines in mvgam |
| mvgam | Fit a Bayesian dynamic GAM to a univariate or multivariate set of time series |
| mvgam-class | Fitted 'mvgam' object description |
| mvgam_diagnostics | Extract diagnostic quantities of 'mvgam' models |
| mvgam_draws | Extract posterior draws from fitted 'mvgam' objects |
| mvgam_families | Supported mvgam families |
| mvgam_forecast-class | 'mvgam_forecast' object description |
| mvgam_formulae | Details of formula specifications in 'mvgam' |
| mvgam_irf-class | 'mvgam_irf' object description |
| mvgam_marginaleffects | Helper functions for mvgam marginaleffects calculations |
| mvgam_trends | Supported mvgam trend models |
| names | Index 'mvgam' objects |
| nb | Supported mvgam families |
| neff_ratio | Extract diagnostic quantities of 'mvgam' models |
| neff_ratio.mvgam | Extract diagnostic quantities of 'mvgam' models |
| nmix | Supported mvgam families |
| nuts_params | Extract diagnostic quantities of 'mvgam' models |
| nuts_params.mvgam | Extract diagnostic quantities of 'mvgam' models |
| pairs.mvgam | Create a matrix of output plots from a 'mvgam' object |
| plot.mvgam | Default mvgam plots |
| plot.mvgam_conditional_effects | Display Conditional Effects of Predictors |
| plot.mvgam_forecast | Plot mvgam posterior predictions for a specified series |
| plot.mvgam_irf | Plot impulse responses from an mvgam_irf object This function takes an 'mvgam_irf' object and produces plots of Impulse Response Functions |
| plot.mvgam_lfo | Plot Pareto-k and ELPD values from a leave-future-out object |
| plot_mvgam_factors | Latent factor summaries for a fitted mvgam object |
| plot_mvgam_fc | Plot mvgam posterior predictions for a specified series |
| plot_mvgam_forecasts | Plot mvgam posterior predictions for a specified series |
| plot_mvgam_pterms | Plot mvgam parametric term partial effects |
| plot_mvgam_randomeffects | Plot mvgam random effect terms |
| plot_mvgam_resids | Residual diagnostics for a fitted mvgam object |
| plot_mvgam_series | Plot observed time series used for mvgam modelling |
| plot_mvgam_smooth | Plot mvgam smooth terms |
| plot_mvgam_trend | Plot mvgam latent trend for a specified series |
| plot_mvgam_uncertainty | Plot mvgam forecast uncertainty contributions for a specified series |
| portal_data | Portal Project rodent capture survey data |
| posterior_epred.mvgam | Draws from the Expected Value of the Posterior Predictive Distribution |
| posterior_linpred.mvgam | Posterior Draws of the Linear Predictor |
| posterior_predict.mvgam | Draws from the Posterior Predictive Distribution |
| ppc | Plot mvgam posterior predictive checks for a specified series |
| ppc.mvgam | Plot mvgam posterior predictive checks for a specified series |
| pp_check | Posterior Predictive Checks for 'mvgam' Objects |
| pp_check.mvgam | Posterior Predictive Checks for 'mvgam' Objects |
| Predict.matrix.mod.smooth | Monotonic splines in mvgam |
| Predict.matrix.moi.smooth | Monotonic splines in mvgam |
| predict.mvgam | Predict from the GAM component of an mvgam model |
| print.mvgam | Summary for a fitted mvgam object |
| print.mvgam_conditional_effects | Display Conditional Effects of Predictors |
| PW | Specify piecewise linear or logistic trends |
| residuals.mvgam | Posterior draws of 'mvgam' residuals |
| rhat | Extract diagnostic quantities of 'mvgam' models |
| rhat.mvgam | Extract diagnostic quantities of 'mvgam' models |
| roll_eval_mvgam | Evaluate forecasts from fitted mvgam objects |
| RW | Specify autoregressive dynamic processes |
| score | Compute probabilistic forecast scores for mvgam objects |
| score.mvgam_forecast | Compute probabilistic forecast scores for mvgam objects |
| series_to_mvgam | This function converts univariate or multivariate time series ('xts' or 'ts' objects) to the format necessary for 'mvgam' |
| set_coef.mvgam | Helper functions for mvgam marginaleffects calculations |
| sim_mvgam | Simulate a set of time series for mvgam modelling |
| smooth.construct.mod.smooth.spec | Monotonic splines in mvgam |
| smooth.construct.moi.smooth.spec | Monotonic splines in mvgam |
| stancode.mvgam | Stan code and data objects for mvgam models |
| stancode.mvgam_prefit | Stan code and data objects for mvgam models |
| standata.mvgam_prefit | Stan code and data objects for mvgam models |
| student | Supported mvgam families |
| student_t | Supported mvgam families |
| summary.mvgam | Summary for a fitted mvgam object |
| summary.mvgam_prefit | Summary for a fitted mvgam object |
| their | Index 'mvgam' objects |
| tweedie | Supported mvgam families |
| update.mvgam | Update an existing 'mvgam' object |
| VAR | Specify autoregressive dynamic processes |
| variables | Index 'mvgam' objects |
| variables.mvgam | Index 'mvgam' objects |
| `mgcv` | Index 'mvgam' objects |