Merge pull request #72 from nicholasjclark/re_export_brms

Re export brms

DESCRIPTION

@@ -1,16 +1,16 @@
 Package: mvgam
 Title: Multivariate (Dynamic) Generalized Additive Models
 Version: 1.1.3
-Date: 2024-07-02
+Date: 2024-09-03
 Authors@R: person("Nicholas J", "Clark", , "nicholas.j.clark1214@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-7131-3301"))
 Description: Fit Bayesian Dynamic Generalized Additive Models to sets of time series. Users can build dynamic nonlinear State-Space models that can incorporate semiparametric effects in observation and process components, using a wide range of observation families. Estimation is performed using Markov Chain Monte Carlo with Hamiltonian Monte Carlo in the software 'Stan'. References: Clark & Wells (2022) <doi:10.1111/2041-210X.13974>.
 URL: https://github.com/nicholasjclark/mvgam, https://nicholasjclark.github.io/mvgam/
 BugReports: https://github.com/nicholasjclark/mvgam/issues
 License: MIT + file LICENSE
 Depends: 
-    R (>= 3.6.0),
-    brms (>= 2.21.0)
+    R (>= 3.6.0)
 Imports: 
+    brms (>= 2.21.0),
     methods,
     mgcv (>= 1.8-13),
     insight (>= 0.19.1),

NAMESPACE

@@ -27,6 +27,7 @@ S3method(get_data,mvgam_prefit)
 S3method(get_predict,mvgam)
 S3method(get_vcov,mvgam)
 S3method(hindcast,mvgam)
+S3method(irf,mvgam)
 S3method(lfo_cv,mvgam)
 S3method(logLik,mvgam)
 S3method(log_posterior,mvgam)
@@ -41,6 +42,7 @@ S3method(pairs,mvgam)
 S3method(plot,mvgam)
 S3method(plot,mvgam_conditional_effects)
 S3method(plot,mvgam_forecast)
+S3method(plot,mvgam_irf)
 S3method(plot,mvgam_lfo)
 S3method(posterior_epred,mvgam)
 S3method(posterior_linpred,mvgam)
@@ -73,9 +75,14 @@ export(PW)
 export(RW)
 export(VAR)
 export(add_residuals)
+export(bernoulli)
+export(beta_binomial)
 export(betar)
 export(code)
 export(compare_mvgams)
+export(comparisons)
+export(conditional_effects)
+export(datagrid)
 export(drawDotmvgam)
 export(dynamic)
 export(ensemble)
@@ -85,14 +92,22 @@ export(eval_smoothDotmodDotsmooth)
 export(eval_smoothDotmoiDotsmooth)
 export(forecast)
 export(get_mvgam_priors)
+export(gp)
 export(hindcast)
+export(hypotheses)
+export(irf)
 export(lfo_cv)
+export(lognormal)
+export(loo)
+export(loo_compare)
 export(lv_correlations)
+export(mcmc_plot)
 export(mvgam)
 export(nb)
 export(neff_ratio)
 export(nmix)
 export(nuts_params)
+export(plot_comparisons)
 export(plot_mvgam_factors)
 export(plot_mvgam_fc)
 export(plot_mvgam_pterms)
@@ -102,13 +117,30 @@ export(plot_mvgam_series)
 export(plot_mvgam_smooth)
 export(plot_mvgam_trend)
 export(plot_mvgam_uncertainty)
+export(plot_predictions)
+export(plot_slopes)
+export(posterior_epred)
+export(posterior_linpred)
+export(posterior_predict)
 export(pp_check)
 export(ppc)
+export(predictions)
+export(prior)
+export(prior_)
+export(prior_string)
+export(rhat)
 export(roll_eval_mvgam)
+export(s)
 export(score)
 export(series_to_mvgam)
+export(set_prior)
 export(sim_mvgam)
+export(slopes)
+export(stancode)
+export(standata)
+export(student)
 export(student_t)
+export(t2)
 export(te)
 export(ti)
 export(tweedie)
@@ -122,22 +154,27 @@ importFrom(bayesplot,neff_ratio)
 importFrom(bayesplot,nuts_params)
 importFrom(bayesplot,pp_check)
 importFrom(brms,bernoulli)
+importFrom(brms,beta_binomial)
 importFrom(brms,conditional_effects)
 importFrom(brms,dbeta_binomial)
 importFrom(brms,do_call)
 importFrom(brms,dstudent_t)
 importFrom(brms,get_prior)
+importFrom(brms,gp)
 importFrom(brms,logm1)
 importFrom(brms,lognormal)
 importFrom(brms,mcmc_plot)
 importFrom(brms,ndraws)
 importFrom(brms,pbeta_binomial)
+importFrom(brms,prior)
+importFrom(brms,prior_)
 importFrom(brms,prior_string)
 importFrom(brms,pstudent_t)
 importFrom(brms,qstudent_t)
 importFrom(brms,rbeta_binomial)
 importFrom(brms,read_csv_as_stanfit)
 importFrom(brms,rstudent_t)
+importFrom(brms,set_prior)
 importFrom(brms,stancode)
 importFrom(brms,standata)
 importFrom(brms,student)
@@ -171,11 +208,18 @@ importFrom(loo,is.loo)
 importFrom(loo,loo)
 importFrom(loo,loo_compare)
 importFrom(magrittr,"%>%")
+importFrom(marginaleffects,comparisons)
+importFrom(marginaleffects,datagrid)
 importFrom(marginaleffects,get_coef)
 importFrom(marginaleffects,get_predict)
 importFrom(marginaleffects,get_vcov)
+importFrom(marginaleffects,hypotheses)
+importFrom(marginaleffects,plot_comparisons)
 importFrom(marginaleffects,plot_predictions)
+importFrom(marginaleffects,plot_slopes)
+importFrom(marginaleffects,predictions)
 importFrom(marginaleffects,set_coef)
+importFrom(marginaleffects,slopes)
 importFrom(methods,cbind2)
 importFrom(mgcv,Predict.matrix)
 importFrom(mgcv,Rrank)
@@ -186,8 +230,12 @@ importFrom(mgcv,get.var)
 importFrom(mgcv,initial.sp)
 importFrom(mgcv,interpret.gam)
 importFrom(mgcv,nb)
+importFrom(mgcv,s)
 importFrom(mgcv,smooth.construct)
 importFrom(mgcv,smoothCon)
+importFrom(mgcv,t2)
+importFrom(mgcv,te)
+importFrom(mgcv,ti)
 importFrom(parallel,clusterEvalQ)
 importFrom(parallel,clusterExport)
 importFrom(parallel,setDefaultCluster)

NEWS.md

@@ -4,6 +4,7 @@
 * Added `standata.mvgam_prefit`, `stancode.mvgam` and `stancode.mvgam_prefit` methods for better alignment with 'brms' workflows
 * Added 'gratia' to *Enhancements* to allow popular methods such as `draw()` to be used for 'mvgam' models if 'gratia' is already installed
 * Added an `ensemble.mvgam_forecast` method to generate evenly weighted combinations of probabilistic forecast distributions
+* Added an `irf.mvgam` method to compute Generalized and Orthogonalized Impulse Response Functions (IRFs) from models fit with Vector Autoregressive dynamics
 
 ## Deprecations
 * The `drift` argument has been deprecated. It is now recommended for users to include parametric fixed effects of "time" in their respective GAM formulae to capture any expected drift effects

R/backends.R

@@ -197,7 +197,8 @@
                                                          'sigma_obs_vec',
                                                          'shape_vec',
                                                          'phi_inv',
-                                                         'lv_coefs_raw'),
+                                                         'lv_coefs_raw',
+                                                         'L_Sigma'),
                                              algorithm = algorithm)
   }
 

R/conditional_effects.R

@@ -2,9 +2,7 @@
 #'
 #' Display conditional effects of one or more numeric and/or categorical
 #' predictors in `mvgam` models, including two-way interaction effects.
-#' @importFrom brms conditional_effects
 #' @importFrom ggplot2 scale_colour_discrete scale_fill_discrete theme_classic
-#' @importFrom marginaleffects plot_predictions
 #' @importFrom graphics plot
 #' @importFrom grDevices devAskNewPage
 #' @inheritParams brms::conditional_effects.brmsfit
@@ -219,6 +217,10 @@ conditional_effects.mvgam = function(x,
   return(out)
 }
 
+#' @export
+#' @importFrom brms conditional_effects
+brms::conditional_effects
+
 #' @rdname conditional_effects.mvgam
 #' @export
 plot.mvgam_conditional_effects = function(x,

R/families.R

@@ -2,7 +2,7 @@
 #' @importFrom stats make.link dgamma pgamma rgamma qnorm plnorm runif pbeta dlnorm dpois
 #' @importFrom stats pnorm ppois plogis gaussian poisson Gamma dnbinom rnbinom dnorm dbeta
 #' @importFrom stats binomial rbinom pbinom dbinom qbinom qlogis
-#' @importFrom brms lognormal student bernoulli rstudent_t qstudent_t dstudent_t pstudent_t dbeta_binomial rbeta_binomial pbeta_binomial
+#' @importFrom brms lognormal student beta_binomial bernoulli rstudent_t qstudent_t dstudent_t pstudent_t dbeta_binomial rbeta_binomial pbeta_binomial
 #' @importFrom mgcv betar nb
 #' @param link a specification for the family link function. At present these cannot
 #' be changed
@@ -80,6 +80,30 @@ nb = function(...){
   mgcv::nb(...)
 }
 
+#' @rdname mvgam_families
+#' @export
+lognormal = function(...){
+  brms::lognormal(...)
+}
+
+#' @rdname mvgam_families
+#' @export
+student = function(...){
+  brms::student(...)
+}
+
+#' @rdname mvgam_families
+#' @export
+bernoulli = function(...){
+  brms::bernoulli(...)
+}
+
+#' @rdname mvgam_families
+#' @export
+beta_binomial = function(...){
+  brms::beta_binomial(...)
+}
+
 #' @rdname mvgam_families
 #' @examples
 #' \donttest{

R/get_mvgam_priors.R

@@ -1254,6 +1254,22 @@ get_mvgam_priors = function(formula,
   return(out)
 }
 
+#' @export
+#' @importFrom brms prior
+brms::prior
+
+#' @export
+#' @importFrom brms prior_
+brms::prior_
+
+#' @export
+#' @importFrom brms set_prior
+brms::set_prior
+
+#' @export
+#' @importFrom brms prior_string
+brms::prior_string
+
 #' Use informative scale and intercept priors following brms example
 #' @importFrom stats mad qcauchy setNames
 #' @importFrom brms logm1 prior_string get_prior