The function appends the second model output tibble to the first while keeping all variables from both tibbles.
merge_models(mod_tbl1, mod_tbl2)
| mod_tbl1 | Model output tibble created e.g. with |
|---|---|
| mod_tbl2 | Model output tibble created e.g. with |
merge_models returns the same type as the input including all columns of
both tibbles.
merge_models function applies internally the dplyr::bind_rows function so that columns
are matched by name, and any missing columns will be filled with NA. The function
has also some data validation incorporated to check for double entries.
if (FALSE) { # Using some models of the Baltic Sea demo data: # Merging GAM and GAMM tibbles test_ids <- 47:50 # choose subset gam_tbl <- model_gam_ex[test_ids,] gamm_tbl <- model_gamm(ind_init_ex[test_ids,], filter= gam_tbl$tac) best_gamm <- select_model(gam_tbl, gamm_tbl) merge_models(gam_tbl[gam_tbl$tac == FALSE,], best_gamm) # Merge 2 IND-specific GAM tibbles (where) dat_init <- ind_init( ind_tbl = ind_ex[, c("TZA", "Cod")], press_tbl = press_ex[, c("Tsum", "Swin")], time = ind_ex[,1]) gam_tbl1 <- model_gam(dat_init[1:2, ]) # treat a subset differently, e.g. when setting k gam_tbl2 <- model_gam(dat_init[3:4, ], k = 3) merge_models(gam_tbl1, gam_tbl2) }