Summarizes the scoring output tibble so that IND-specific scores for each criterion as well as the pressure-specific sub-criteria scores (in crit. 9 and 10) can be easily compared and used for further score-based IND performance functions.

summary_sc(scores_tbl, crit_scores = INDperform::crit_scores_tmpl)

Arguments

scores_tbl

The output tibble from the scoring function.

crit_scores

The (un)modified criterion-scoring template crit_scores_tmpl; required to calculate the scores in percentage. Has to be the same than used in scoring. Default is the unmodified template crit_scores_tmpl.

Value

The function returns a list of 3 data frames

overview

IND-specific scores and percentages from max. score for all criteria (crit 9 and 10 averaged across all sign. pressures and the number of significant pressures).

subcriteria_per_press

IND- and pressure-specific scores for all (sub-)criteria and the percentages from max. criterion score.

scores_matrix

TEXT

See also

Other score-based IND performance functions: clust_sc(), dist_sc_group(), dist_sc(), expect_resp(), plot_clust_sc(), plot_spiechart(), scoring()

Examples

# Using the Baltic Sea demo data in this package scores_tbl <- scoring(trend_tbl = model_trend_ex, mod_tbl = all_results_ex, press_type = press_type_ex) summary_sc(scores_tbl)
#> $overview #> ind nr_sign_press C8 C9 C10 C11 C8_in% C9_in% C10_in% C11_in% #> 1 TZA 2 0 5.0 2.0 2 0 83 33 100 #> 2 MS 2 0 4.0 2.5 1 0 67 42 50 #> 3 rCC 1 0 6.0 4.0 2 0 100 67 100 #> 4 Cops 0 0 0.0 0.0 0 0 0 0 0 #> 5 Micro 2 1 5.0 4.0 1 100 83 67 50 #> 6 rZPPP 1 0 4.0 5.0 2 0 67 83 100 #> 7 Sprat 1 1 2.0 1.0 2 100 33 17 100 #> 8 Herring 0 1 0.0 0.0 0 100 0 0 0 #> 9 Stickle 0 1 0.0 0.0 0 100 0 0 0 #> 10 Cod 2 1 4.5 1.5 2 100 75 25 100 #> 11 SPF 1 1 5.0 4.0 2 100 83 67 100 #> 12 LPF 1 1 5.0 5.0 2 100 83 83 100 #> #> $subcriteria_per_press #> ind press press_type C9_1 C9_2 C10_1 C10_2 C10_3 C10_4 C9 C10 C9_in% #> 1 TZA Fsprat Fishing 3 3 1 0 0 0 6 1 100 #> 2 TZA Fher Fishing 1 3 1 1 1 0 4 3 67 #> 3 MS Swin Climate 2 2 1 0 1 1 4 3 67 #> 4 MS Fher Fishing 1 3 1 1 0 0 4 2 67 #> 5 rCC Tsum Climate 3 3 1 1 1 1 6 4 100 #> 6 Micro Tsum Climate 2 3 1 1 2 1 5 5 83 #> 7 Micro Fsprat Fishing 2 3 1 0 2 0 5 3 83 #> 8 rZPPP Tsum Climate 1 3 1 1 2 1 4 5 67 #> 9 Sprat Fher Fishing 2 0 1 0 0 0 2 1 33 #> 10 Cod Fher Fishing 3 3 1 0 0 0 6 1 100 #> 11 Cod Fcod Fishing 2 1 1 0 1 0 3 2 50 #> 12 SPF Pwin Eutrophication 2 3 1 1 1 1 5 4 83 #> 13 LPF Fcod Fishing 2 3 1 1 2 1 5 5 83 #> C10_in% #> 1 17 #> 2 50 #> 3 50 #> 4 33 #> 5 67 #> 6 83 #> 7 50 #> 8 83 #> 9 17 #> 10 17 #> 11 33 #> 12 67 #> 13 83 #> #> $scores_matrix #> C8 C11 Fcod_C10 Fcod_C9 Fher_C10 Fher_C9 Fsprat_C10 Fsprat_C9 Nwin_C10 #> TZA 0 2 0 0 3 4 1 6 0 #> MS 0 1 0 0 2 4 0 0 0 #> rCC 0 2 0 0 0 0 0 0 0 #> Cops 0 0 0 0 0 0 0 0 0 #> Micro 1 1 0 0 0 0 3 5 0 #> rZPPP 0 2 0 0 0 0 0 0 0 #> Sprat 1 2 0 0 1 2 0 0 0 #> Herring 1 0 0 0 0 0 0 0 0 #> Stickle 1 0 0 0 0 0 0 0 0 #> Cod 1 2 2 3 1 6 0 0 0 #> SPF 1 2 0 0 0 0 0 0 0 #> LPF 1 2 5 5 0 0 0 0 0 #> Nwin_C9 Pwin_C10 Pwin_C9 Swin_C10 Swin_C9 Tsum_C10 Tsum_C9 #> TZA 0 0 0 0 0 0 0 #> MS 0 0 0 3 4 0 0 #> rCC 0 0 0 0 0 4 6 #> Cops 0 0 0 0 0 0 0 #> Micro 0 0 0 0 0 5 5 #> rZPPP 0 0 0 0 0 5 4 #> Sprat 0 0 0 0 0 0 0 #> Herring 0 0 0 0 0 0 0 #> Stickle 0 0 0 0 0 0 0 #> Cod 0 0 0 0 0 0 0 #> SPF 0 4 5 0 0 0 0 #> LPF 0 0 0 0 0 0 0 #>