expect_resp runs a shiny app in which the expectation of the IND response to
a pressure (sub-criterion 10.1) can be manually changed to `yes` or `no` based on
visual inspection of the IND response curve.
expect_resp(mod_tbl, scores_tbl, crit_scores = INDperform::crit_scores_tmpl)
| mod_tbl | Output tibble from the IND~pressure modeling functions. |
|---|---|
| scores_tbl | The output tibble from the |
| crit_scores | The(un)modified criterion-scoring template |
The function returns the input scoring tibble, but with modified scores
in the variable C10_1, once the "Press Me!" button is activated.
The sub-criterion 10.1 (i.e. the IND response to a pressure, which has been found significant,
is in line with expectations based on ecological knowledge) has been set
to a default score of 1 (no expectation / unclear as response is highly non-linear)
in the scoring function. Determining whether the IND response modeled in
the GAM/GAMM meets specific expectations can only be done
based on visual model inspections. expect_resp provides only a very simple
graphical representation of this smoothing function.
For a more comprehensive figure use the plot_model
function and then go back to this function for modifications
of the expectation scores.
plot_model for visualization of the IND responses to pressures
Other score-based IND performance functions:
clust_sc(),
dist_sc_group(),
dist_sc(),
plot_clust_sc(),
plot_spiechart(),
scoring(),
summary_sc()
if (FALSE) { # Using the Baltic Sea demo data: # Apply first the scoring on the model outputs scores_tbl <- scoring(trend_tbl = model_trend_ex, mod_tbl = all_results_ex, press_type = press_type_ex) # Then run the expect_resp() shiny function to correct one criterion scores_tbl <- expect_resp(all_results_ex, scores_tbl) # Check if it worked: expect_resp(all_results_ex, scores_tbl) }