Use custom intercept variable instead of R function default intercept.

Author: njhenry

R/generate_cell_draws_and_summarize.R

@@ -100,7 +100,7 @@ generate_cell_draws_and_summarize <- function(
     fe_coefficients <- latent_matrix[param_names == 'covariates', ]
     fe_draws <- as.matrix(id_raster_table[, cov_names, with = F]) %*% fe_coefficients
   } else {
-    fe_draws <- latent_matrix[param_names == '(Intercept)', ] |>
+    fe_draws <- latent_matrix[param_names == 'Intercept', ] |>
       matrix(ncol = n_samples, nrow = nrow(transformed_cell_draws), byrow = TRUE)
   }
   transformed_cell_draws <- transformed_cell_draws + fe_draws

R/prepare_inla_data_stack.R

@@ -121,7 +121,9 @@ prepare_inla_data_stack <- function(
       "y ~ 0 + f(covariates, model = 'iid', fixed = TRUE{constraint_suffix})"
     )
   } else {
-    formula_string <- "y ~ 1"
+    formula_string <- "y ~ 0 + Intercept"
+    effects_list$Intercept <- 1
+    obs_list$Intercept <- rep(1, nrow(input_data))
   }
 
   ## Optionally add the SPDE approximation to a Gaussian process