add check on CAR1 for trend mapping

nicholasjclark · Dec 3, 2024 · ba9cb2d · ba9cb2d
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diff --git a/R/how_to_cite.R b/R/how_to_cite.R
@@ -239,7 +239,7 @@ how_to_cite.mvgam <- function(object, ...){
 
   # List of additional, possibly very useful references
   other_citations <- vector(mode = 'list')
-  other_citations[[1]] <- "Arel-Bundock V (2024). marginaleffects: Predictions, Comparisons, Slopes, Marginal Means, and Hypothesis Tests. R package version 0.19.0.4, https://marginaleffects.com/."
+  other_citations[[1]] <- "Arel-Bundock, V, Greifer, N, and Heiss, A (2024). How to interpret statistical models using marginaleffects for R and Python. Journal of Statistical Software, 111(9), 1–32. https://doi.org/10.18637/jss.v111.i09"
   other_citations[[2]] <- "Gabry J, Simpson D, Vehtari A, Betancourt M, and Gelman A (2019). Visualization in Bayesian workflow. Journal of the Royal Statatistical Society A, 182, 389-402. doi:10.1111/rssa.12378."
   other_citations[[3]] <- "Vehtari A, Gelman A, and Gabry J (2017). Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC. Statistics and Computing, 27, 1413-1432. doi:10.1007/s11222-016-9696-4."
   other_citations[[4]] <- "Burkner, PC, Gabry, J, and Vehtari, A. (2020). Approximate leave-future-out cross-validation for Bayesian time series models. Journal of Statistical Computation and Simulation, 90(14), 2499-2523. https://doi.org/10.1080/00949655.2020.1783262"

diff --git a/R/mvgam.R b/R/mvgam.R
@@ -132,6 +132,7 @@
 #'should depend on. The `series` column should have a single unique entry for each series in the
 #'data (names should perfectly match factor levels of the `series` variable in `data`). Note that
 #'if this is supplied, the intercept parameter in the process model will NOT be automatically suppressed.
+#'Not yet supported for models in wich the latent factors evolve in continuous time (`CAR()`).
 #'See examples for details
 #'@param noncentred \code{logical} Use the non-centred parameterisation for autoregressive
 #'trend models? Setting to `TRUE` will reparameterise the model to avoid possible

diff --git a/R/validations.R b/R/validations.R
@@ -666,11 +666,11 @@ validate_trendmap = function(trend_map,
          call. = FALSE)
   }
 
-  # No point in trend mapping if trend model is 'None'
-  # if(trend_model == 'None'){
-  #   stop('cannot set up latent trends when "trend_model = None"',
-  #        call. = FALSE)
-  # }
+  # Cannot yet map observations to trends that evolve as CAR1
+  if(trend_model == 'CAR1'){
+    stop('cannot yet use trend mapping for CAR1 dynamics',
+         call. = FALSE)
+  }
 
   # trend_map must have an entry for each unique time series
   if(!all(sort(trend_map$series) == sort(unique(data_train$series)))){

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