Function reference

All functions

GP()

Specify dynamic Gaussian process trends inmvgam models

RW()AR()CAR()VAR()

Specify autoregressive dynamic processes inmvgam

ZMVN()

Specify correlated residual processes inmvgam

add_residuals()

Calculate randomized quantile residuals formvgam objects

all_neon_tick_data

NEON Amblyomma and Ixodes tick abundance survey data

augment(<mvgam>)

Augment anmvgam object's data

code()stancode(<mvgam_prefit>)stancode(<mvgam>)standata(<mvgam_prefit>)

Stan code and data objects formvgam models

conditional_effects(<mvgam>)plot(<mvgam_conditional_effects>)print(<mvgam_conditional_effects>)

Display conditional effects of predictors formvgam models

dynamic()

Defining dynamic coefficients inmvgam formulae

ensemble()

Combine forecasts frommvgam models into evenly weighted ensembles

eval_mvgam()roll_eval_mvgam()compare_mvgams()

Evaluate forecasts from fittedmvgam objects

fevd()

Calculate latent VAR forecast error variance decompositions

fitted(<mvgam>)

Expected values of the posterior predictive distribution formvgam objects

forecast(<mvgam>)

Extract or compute hindcasts and forecasts for a fittedmvgam object

formula(<mvgam>)formula(<mvgam_prefit>)

Extract formulae frommvgam objects

get_mvgam_priors()

Extract information on default prior distributions for anmvgam model

drawDotmvgam()eval_smoothDothilbertDotsmooth()eval_smoothDotmodDotsmooth()eval_smoothDotmoiDotsmooth()

Enhance post-processing ofmvgam models usinggratia functionality

hindcast()

Extract hindcasts for a fittedmvgam object

how_to_cite()

Generate a methods description formvgam models

variables(<mvgam>)

Indexmvgam objects

irf()

Calculate latent VAR impulse response functions

jsdgam()

Fit Joint Species Distribution Models inmvgam

lfo_cv()

Approximate leave-future-out cross-validation of fittedmvgam objects

logLik(<mvgam>)

Compute pointwise Log-Likelihoods from fittedmvgam objects

loo(<mvgam>)loo_compare(<mvgam>)

LOO information criteria formvgam models

lv_correlations()

Calculate trend correlations based on latent factor loadings formvgam models

mcmc_plot(<mvgam>)

MCMC plots ofmvgam parameters, as implemented inbayesplot

model.frame(<mvgam>)model.frame(<mvgam_prefit>)

Extract model.frame from a fittedmvgam object

smooth.construct(<moi.smooth.spec>)smooth.construct(<mod.smooth.spec>)Predict.matrix(<moi.smooth>)Predict.matrix(<mod.smooth>)

Monotonic splines inmvgam models

mvgam-class

Fittedmvgam object description

mvgam()

Fit a Bayesian Dynamic GAM to Univariate or Multivariate Time Series

nuts_params(<mvgam>)log_posterior(<mvgam>)rhat(<mvgam>)neff_ratio(<mvgam>)

Extract diagnostic quantities ofmvgam models

as.data.frame(<mvgam>)as.matrix(<mvgam>)as.array(<mvgam>)as_draws(<mvgam>)as_draws_matrix(<mvgam>)as_draws_df(<mvgam>)as_draws_array(<mvgam>)as_draws_list(<mvgam>)as_draws_rvars(<mvgam>)

Extract posterior draws from fittedmvgam objects

tweedie()student_t()betar()nb()lognormal()student()bernoulli()beta_binomial()nmix()

Supportedmvgam families

mvgam_fevd-class

mvgam_fevd object description

mvgam_forecast-class

mvgam_forecast object description

mvgam_formulae

Details of formula specifications inmvgam models

mvgam_irf-class

mvgam_irf object description

get_coef(<mvgam>)set_coef(<mvgam>)get_vcov(<mvgam>)get_predict(<mvgam>)get_data(<mvgam>)get_data(<mvgam_prefit>)find_predictors(<mvgam>)find_predictors(<mvgam_prefit>)

Helper functions formarginaleffects calculations inmvgam models

mvgam_residcor-class

mvgam_residcor object description

mvgam_trends

Supported latent trend models inmvgam

mvgam_use_cases

Example use cases formvgam

ordinate()

Latent variable ordination plots from jsdgam objects

pairs(<mvgam>)

Create a matrix of output plots from amvgam object

PW()

Specify piecewise linear or logistic trends inmvgam models

plot(<mvgam>)

Default plots formvgam models

plot(<mvgam_fevd>)

Plot forecast error variance decompositions from anmvgam_fevd object

plot(<mvgam_irf>)

Plot impulse responses from anmvgam_irf object

plot(<mvgam_lfo>)

Plot Pareto-k and ELPD values from amvgam_lfo object

plot(<mvgam_residcor>)

Plot residual correlations based on latent factors

plot_mvgam_factors()

Latent factor summaries for a fittedmvgam object

plot_mvgam_fc()plot(<mvgam_forecast>)

Plot posterior forecast predictions frommvgam models

plot_mvgam_pterms()

Plot parametric term partial effects formvgam models

plot_mvgam_randomeffects()

Plot random effect terms frommvgam models

plot_mvgam_resids()

Residual diagnostics for a fittedmvgam object

plot_mvgam_series()

Plot observed time series used formvgam modelling

plot_mvgam_smooth()

Plot smooth terms frommvgam models

plot_mvgam_trend()

Plot latent trend predictions frommvgam models

plot_mvgam_uncertainty()

Plot forecast uncertainty contributions frommvgam models

portal_data

Portal Project rodent capture survey data

posterior_epred(<mvgam>)

Draws from the expected value of the posterior predictive distribution formvgam objects

posterior_linpred(<mvgam>)

Posterior draws of the linear predictor formvgam objects

posterior_predict(<mvgam>)

Draws from the posterior predictive distribution formvgam objects

pp_check(<mvgam>)

Posterior Predictive Checks formvgam models

ppc()

Plot conditional posterior predictive checks frommvgam models

predict(<mvgam>)

Predict from a fittedmvgam model

print(<mvgam>)

Print a fittedmvgam object

print(<mvgam_summary>)

Print method for mvgam_summary objects

residual_cor()

Extract residual correlations based on latent factors

residuals(<mvgam>)

Posterior draws of residuals frommvgam models

score()

Compute probabilistic forecast scores formvgam models

series_to_mvgam()

Convert timeseries object to format necessary formvgam models

sim_mvgam()

Simulate a set of time series for modelling inmvgam

stability()

Calculate measures of latent VAR community stability

summary(<mvgam>)summary(<mvgam_prefit>)coef(<mvgam>)

Summary for a fittedmvgam models

summary(<mvgam_fevd>)

Posterior summary of forecast error variance decompositions

summary(<mvgam_forecast>)

Posterior summary of hindcast and forecast objects

summary(<mvgam_irf>)

Posterior summary of impulse responses

tidy(<mvgam>)

Tidy anmvgam object's parameter posteriors

update(<mvgam>)update(<jsdgam>)

Update an existingmvgam model object