SD.RdFind the standard deviation of a vector, matrix, or data.frame. In the latter two cases, return the sd of each column. Unlike the sd function, return NA if there are no observations rather than throw an error.
SD(x, na.rm = TRUE) #deprecatedFinds the standard deviation of a vector, matrix, or data.frame. Returns NA if no cases.
Just an adaptation of the stats:sd function to return the functionality found in R < 2.7.0 or R >= 2.8.0 Because this problem seems to have been fixed, SD will be removed eventually.
The standard deviation
Until R 2.7.0, sd would return a NA rather than an error if no cases were observed. SD brings back that functionality. Although unusual, this condition will arise when analyzing data with high rates of missing values. This function will probably be removed as 2.7.0 becomes outdated.
These functions use SD rather than sd: describe.by, skew, kurtosi
data(attitude)
apply(attitude,2,sd) #all complete
#> rating complaints privileges learning raises critical advance
#> 12.172562 13.314757 12.235430 11.737013 10.397226 9.894908 10.288706
attitude[,1] <- NA
SD(attitude) #missing a column
#> rating complaints privileges learning raises critical advance
#> NA 13.314757 12.235430 11.737013 10.397226 9.894908 10.288706
describe(attitude)
#> Warning: no non-missing arguments to min; returning Inf
#> Warning: no non-missing arguments to max; returning -Inf
#> vars n mean sd median trimmed mad min max range skew
#> rating 1 0 NaN NA NA NaN NA Inf -Inf -Inf NA
#> complaints 2 30 66.60 13.31 65.0 67.08 14.83 37 90 53 -0.22
#> privileges 3 30 53.13 12.24 51.5 52.75 10.38 30 83 53 0.38
#> learning 4 30 56.37 11.74 56.5 56.58 14.83 34 75 41 -0.05
#> raises 5 30 64.63 10.40 63.5 64.50 11.12 43 88 45 0.20
#> critical 6 30 74.77 9.89 77.5 75.83 7.41 49 92 43 -0.87
#> advance 7 30 42.93 10.29 41.0 41.83 8.90 25 72 47 0.85
#> kurtosis se
#> rating NA NA
#> complaints -0.68 2.43
#> privileges -0.41 2.23
#> learning -1.22 2.14
#> raises -0.60 1.90
#> critical 0.17 1.81
#> advance 0.47 1.88