merge_models: Merging two model output tibbles.

In saskiaotto/INDperform: Evaluation of Indicator Performances for Assessing Ecosystem States

Description

The function appends the second model output tibble to the first while keeping all variables from both tibbles.

Usage

merge_models(mod_tbl1, mod_tbl2)

Arguments

mod_tbl1	Model output tibble created e.g. with model_gam.
mod_tbl2	Model output tibble created e.g. with select_model.

Details

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.

Value

merge_models returns the same type as the input including all columns of both tibbles.

Examples

## Not run: 
# 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)

## End(Not run)

saskiaotto/INDperform documentation built on Oct. 27, 2021, 10:33 p.m.