library(PRcalc)
data(jp_upper_2019)
pr_obj <- prcalc(jp_upper_2019, m = 50, method = "dt")
index(pr_obj)
ID Index Value
1 dhondt D’Hondt 1.116833
2 monroe Monroe 0.018918
3 maxdev Maximum Absolute Deviation 0.010461
4 mm_ratio Max-Min ratio Inf
5 rae Rae 0.004664
6 lh Loosemore & Hanby 0.030315
7 grofman Grofman 0.011677
8 lijphart Lijphart 0.004069
9 gallagher Gallagher 0.014609
10 g_gallagher Generalized Gallagher 0.014609
11 gatev Gatev 0.032939
12 ryabtsev Ryabtsev 0.023298
13 szalai Szalai 0.555712
14 w_szalai Weighted Szalai 0.090661
15 ap Aleskerov & Platonov 1.042141
16 gini Gini 0.036069
17 atkinson Atkinson 1.000000
18 sl Sainte-Laguë 0.018466
19 cs Cox & Shugart 1.033646
20 farina Farina 0.046282
21 ortona Ortona 0.046909
22 cd Cosine Dissimilarity 0.000867
23 rr Lebeda’s RR (Mixture D’Hondt) 0.104611
24 arr Lebeda’s ARR 0.008047
25 srr Lebeda’s SRR 0.041482
26 wdrr Lebeda’s WDRR 0.055081
27 kl Kullback-Leibler Surprise 0.016431
28 lr Likelihood Ratio Statistic Inf
29 chisq Chi Squared 0.004225
30 hellinger Hellinger Distance 0.087758
31 ad alpha-Divergence 0.009233
index(pr_obj) |>
print(subset = c("lh", "gallagher", "rae", "dhondt", "ad"))
ID Index Value
1 dhondt D’Hondt 1.11683
2 rae Rae 0.00466
3 lh Loosemore & Hanby 0.03032
4 gallagher Gallagher 0.01461
5 ad alpha-Divergence 0.00923