Compares two coin class objects using a specified iCode (column of data) from specified data sets.
Usage
compare_coins(
coin1,
coin2,
dset,
iCode,
also_get = NULL,
compare_by = "ranks",
sort_by = NULL,
decreasing = FALSE
)Arguments
- coin1
A coin class object
- coin2
A coin class object
- dset
A data set that is found in
.$Data.- iCode
The name of a column that is found in
.$Data[[dset]].- also_get
Optional metadata columns to attach to the table: see
get_data().- compare_by
Either
"ranks"which produces a comparison using ranks, or else"scores", which instead uses scores. Note that scores may be very different if the methodology is different from one coin to another, e.g. for different normalisation methods.- sort_by
Optionally, a column name of the output data frame to sort rows by. Can be either
"coin.1","coin.2","Diff","Abs.diff"or possibly a column name imported usingalso_get.- decreasing
Argument to pass to
order(): how to sort.
Examples
# build full example coin
coin <- build_example_coin(quietly = TRUE)
# copy coin
coin2 <- coin
# change to prank function (percentile ranks)
# we don't need to specify any additional parameters (f_n_para) here
coin2$Log$Normalise$global_specs <- list(f_n = "n_prank")
# regenerate
coin2 <- Regen(coin2)
# compare index, sort by absolute rank difference
compare_coins(coin, coin2, dset = "Aggregated", iCode = "Index",
sort_by = "Abs.diff", decreasing = TRUE)
#> uCode coin.1 coin.2 Diff Abs.diff
#> 43 PRT 27 17 10 10
#> 29 LAO 48 39 9 9
#> 33 MLT 10 19 -9 9
#> 14 EST 22 16 6 6
#> 21 IDN 43 49 -6 6
#> 13 ESP 19 24 -5 5
#> 19 HRV 18 23 -5 5
#> 30 LTU 16 11 5 5
#> 35 MNG 44 48 -4 4
#> 17 GBR 15 12 3 3
#> 25 JPN 34 31 3 3
#> 32 LVA 23 20 3 3
#> 40 PAK 50 47 3 3
#> 3 BEL 5 7 -2 2
#> 4 BGD 46 44 2 2
#> 8 CHN 49 51 -2 2
#> 20 HUN 20 22 -2 2
#> 23 IRL 12 14 -2 2
#> 26 KAZ 47 45 2 2
#> 28 KOR 31 33 -2 2
#> 31 LUX 8 10 -2 2
#> 37 NLD 2 4 -2 2
#> 41 PHL 38 40 -2 2
#> 42 POL 26 28 -2 2
#> 47 SVK 24 26 -2 2
#> 48 SVN 11 9 2 2
#> 2 AUT 7 6 1 1
#> 5 BGR 30 29 1 1
#> 6 BRN 40 41 -1 1
#> 9 CYP 29 30 -1 1
#> 10 CZE 17 18 -1 1
#> 11 DEU 9 8 1 1
#> 12 DNK 3 2 1 1
#> 22 IND 45 46 -1 1
#> 24 ITA 28 27 1 1
#> 27 KHM 37 36 1 1
#> 34 MMR 41 42 -1 1
#> 36 MYS 39 38 1 1
#> 38 NOR 4 3 1 1
#> 39 NZL 33 34 -1 1
#> 45 RUS 51 50 1 1
#> 46 SGP 14 15 -1 1
#> 49 SWE 6 5 1 1
#> 50 THA 42 43 -1 1
#> 51 VNM 36 37 -1 1
#> 1 AUS 35 35 0 0
#> 7 CHE 1 1 0 0
#> 15 FIN 13 13 0 0
#> 16 FRA 21 21 0 0
#> 18 GRC 32 32 0 0
#> 44 ROU 25 25 0 0