r1sd allows you to rescale a numeric vector such that the
ensuing output has a mean of 0 and a standard deviation of 1.
Arguments
- x
a numeric vector
- na
what to do with NAs in the vector. Defaults to TRUE (i.e. passes over the missing observations)
Value
The function returns a numeric vector rescaled with a mean of 0 and a standard deviation of 1.
Details
This is a convenience function since the default rescale() function
has some additional weirdness that is not welcome for my use cases. By default,
na.rm is set to TRUE.
Examples
x <- rnorm(100)
r1sd(x)
#> [1] 0.8589857352 0.6882792081 -0.3820161132 -0.2185607108 -2.3581866933
#> [6] -1.1186076412 -0.9259636957 0.3993068214 -0.9705208235 0.9448918531
#> [11] -1.9134339921 0.5798526209 0.6713547170 0.2153457412 1.3869096436
#> [16] 0.3956947758 -0.4787230015 0.4141902533 -0.8131107521 -0.9124984890
#> [21] 1.7734287396 1.3392256447 0.1729591211 -1.4489497087 -0.0413043116
#> [26] 0.0220676683 -2.2579591760 -0.7365099747 -1.7214374886 0.9269118133
#> [31] 0.2402823685 -1.5983065925 0.1540897909 0.4292600416 0.5623382525
#> [36] 0.9417246305 0.7862868975 0.4378974028 0.5348330059 1.3801393606
#> [41] -0.0601846493 0.0949865211 1.2914664780 -0.0007232612 0.9247860528
#> [46] -0.1117526441 -0.5317138969 -0.1530381957 0.8195438764 -1.0799893600
#> [51] 0.2095907871 -0.2415049796 2.6475450451 -1.0827106024 -0.3501653160
#> [56] 0.2515200939 1.9588504804 -0.2365637631 0.6123825135 -1.9958963302
#> [61] 0.3751642922 0.9637732620 0.4935186982 0.1102981212 -0.0458281813
#> [66] 0.0081144400 -2.4718601906 0.3977882087 1.1481818390 1.4765321954
#> [71] -0.4463775814 1.2445406548 -0.7944924161 -1.4013223523 1.2760452552
#> [76] -0.5366643254 0.0709421095 -1.0050927198 1.3207408527 1.0405286073
#> [81] 0.4652549313 -0.0473292065 -0.6480720990 0.9625997253 -1.4998238910
#> [86] -0.8196351690 -1.2349042335 0.8690667709 -0.6636137487 -0.9215064628
#> [91] -0.2838803156 -0.1382895314 -0.1508800263 1.0792471933 -0.8381494592
#> [96] 0.5004442955 -0.0965475607 -1.6511651186 0.5083293670 0.0577279770