Logit
and Expit
Transformations
logit.Rd
logit()
computes the binary logit function.
This is a simple wrapper for stats::qlogis()
with default input arguments.
expit()
computes the logistic function. This is a
simple wrapper for stats::plogis()
with
default input arguments.
Examples
x <- stats::runif(n = 100L)
logit(x)
#> [1] 0.499616647 0.222215872 3.206188606 2.384526260 0.419132311
#> [6] -0.792863709 0.221509802 2.709719579 -0.553567354 -0.669395114
#> [11] 1.206525292 -0.840914083 0.530676818 1.401991539 0.169345807
#> [16] 0.536498772 -1.451382622 -1.364853028 2.561634588 -0.349748316
#> [21] -1.892410368 -2.731099366 2.051250092 0.373102779 0.956458537
#> [26] 0.049582150 -0.866089472 0.574401026 2.016739334 2.866213050
#> [31] 0.892552686 2.492588015 -4.105057499 -1.575186380 -1.301041632
#> [36] 1.696791254 -1.134553697 0.060219609 1.842020477 -3.163601445
#> [41] -0.160229022 -1.614210594 2.381224660 -0.366347769 0.577674696
#> [46] -1.622804834 -1.509720990 5.638018577 0.597617075 2.416786278
#> [51] 1.355733750 2.352050632 -0.444960649 -0.586664696 0.465683658
#> [56] -1.434228138 -2.558785246 -0.817790215 -1.553534622 2.068073280
#> [61] -0.008607154 0.818454108 1.938761579 -3.994321971 -0.481122684
#> [66] 0.054385499 -3.004507385 1.405752330 0.549790283 1.215826256
#> [71] 0.007055000 0.901651476 -2.290672822 -2.133229708 -1.237256562
#> [76] -0.332372155 -0.645461223 0.682094271 -0.227521754 -0.818022627
#> [81] -0.997943191 -0.992459294 -2.223162878 4.827864146 -2.147911586
#> [86] -0.263561314 0.775398647 -0.708992392 -0.407370927 0.843284611
#> [91] -1.138896031 -3.564373097 -2.585307333 -3.718153256 -1.345536215
#> [96] 0.842000234 3.964918476 1.275317046 0.428328972 -1.334829022
x <- stats::rnorm(n = 100L)
expit(x)
#> [1] 0.67220730 0.67037577 0.08422289 0.80285992 0.44778835 0.27086282
#> [7] 0.87674563 0.64429293 0.43003811 0.36151700 0.48373187 0.27672924
#> [13] 0.76309071 0.50466473 0.86490666 0.24727768 0.43714232 0.19844013
#> [19] 0.34997444 0.56545077 0.19717980 0.69503211 0.47875879 0.65687092
#> [25] 0.73330410 0.83616052 0.70167462 0.42509901 0.40233219 0.56291118
#> [31] 0.47880150 0.65607527 0.19952215 0.81513553 0.48384594 0.30889985
#> [37] 0.12621082 0.52119832 0.62641703 0.80435700 0.59800028 0.59148417
#> [43] 0.85058998 0.33591770 0.24740875 0.37707682 0.38806429 0.27787346
#> [49] 0.41390425 0.55606917 0.35546083 0.79663048 0.85147011 0.45652341
#> [55] 0.73172590 0.38093061 0.37147765 0.46592229 0.74777098 0.41535921
#> [61] 0.85493609 0.45718300 0.29424395 0.29109899 0.24683678 0.40104008
#> [67] 0.55970473 0.65893331 0.70091548 0.34773503 0.31119260 0.40041903
#> [73] 0.78607232 0.77025160 0.90784389 0.66893335 0.35345974 0.73618781
#> [79] 0.62420125 0.29399052 0.32913709 0.35321616 0.58219920 0.40511532
#> [85] 0.86609034 0.51404752 0.08506075 0.48507245 0.60441016 0.80499353
#> [91] 0.82009260 0.72164714 0.37546645 0.28261653 0.29027780 0.66861990
#> [97] 0.42664754 0.58688937 0.73818406 0.57053062