typo fix

R/forecast.mvgam.R

@@ -202,7 +202,9 @@ forecast.mvgam = function(object,
     names(series_fcs) <- levels(data_test$series)
 
     # Extract hindcasts
-    data_train <- object$obs_data
+    data_train <- validate_series_time(object$obs_data,
+                                       trend_model = attr(object$model_data,
+                                                          'trend_model'))
     ends <- seq(0, dim(mcmc_chains(object$model_output, 'ypred'))[2],
                 length.out = NCOL(object$ytimes) + 1)
     starts <- ends + 1

R/hindcast.mvgam.R

@@ -172,10 +172,10 @@ hindcast.mvgam = function(object,
   names(series_hcs) <- levels(data_train$series)
 
   series_obs <- lapply(seq_len(n_series), function(series){
-    s_name <- levels(object$obs_data$series)[series]
-    data.frame(series = object$obs_data$series,
-               time = object$obs_data$index..time..index,
-               y = object$obs_data$y) %>%
+    s_name <- levels(data_train$series)[series]
+    data.frame(series = data_train$series,
+               time = data_train$index..time..index,
+               y = data_train$y) %>%
       dplyr::filter(series == s_name) %>%
       dplyr::arrange(time) %>%
       dplyr::pull(y)

R/mvgam.R

@@ -322,7 +322,7 @@
 #'mod1 <- mvgam(formula = y ~ s(season, bs = 'cc', k = 6),
 #'              data = dat$data_train,
 #'              trend_model = RW(),
-#'              family = poison(),
+#'              family = poisson(),
 #'              use_stan = TRUE,
 #'              run_model = FALSE)
 #'

R/plot_mvgam_resids.R

@@ -42,7 +42,9 @@ plot_mvgam_resids = function(object, series = 1,
   }
 
   if(!missing("newdata")){
-    data_test <- newdata
+    data_test <- validate_series_time(newdata,
+                                      trend_model = attr(object$model_data,
+                                                         'trend_model'))
   }
 
 # Plotting colours
@@ -55,7 +57,9 @@ c_dark <- c("#8F2727")
 c_dark_highlight <- c("#7C0000")
 
 # Prediction indices for the particular series
-data_train <- object$obs_data
+data_train <- validate_series_time(object$obs_data,
+                                   trend_model = attr(object$model_data,
+                                                      'trend_model'))
 ends <- seq(0, dim(mcmc_chains(object$model_output, 'ypred'))[2],
             length.out = NCOL(object$ytimes) + 1)
 starts <- ends + 1