Comparing Different methods of removing NAs



    MANUAL <- quote(x[!is.na(x)])
    OMIT <-  quote(na.omit(x))
    EXCL <-  quote(na.exclude(x))


# For small x
    N <- 1e2 
    set.seed(1)
    x <- seq(N)
    x[sample(N, 0.1 * N, FALSE)] <- NA

    mbench(MANUAL, OMIT, EXCL, checkEQUAL=FALSE)

  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 
          RESULTS:
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 
 Unit: milliseconds         Number of Repetitions: 200
     expr      min       lq   median       uq      max
 MANUAL : 25.05179 30.71076 32.59693 35.58822 133.7561
   OMIT : 46.05733 54.70537 56.91661 65.47226 158.3359
   EXCL : 46.67783 54.40949 57.20069 62.23509 159.8488


# For Large x
    N <- 1e6 
    set.seed(1)
    x <- seq(N)
    x[sample(N, 0.1 * N, FALSE)] <- NA

    mbench(MANUAL, OMIT, EXCL, checkEQUAL=FALSE)

  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 
          RESULTS:
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 
 Unit: microseconds  Number of Repetitions: 200
     expr    min     lq  median      uq     max
 MANUAL :  1.529  2.417  2.6260  3.1370  17.534
   OMIT : 12.650 15.420 16.6130 20.0225  77.891
   EXCL : 12.829 15.679 17.4155 20.7315 153.385


### now checking with a roll your own function


removeNA <- function(x) {
  x[!is.na(x)]
}

removeNA.withCheck <- function(x) {
  if(!is.atomic(x))
    stop("`x` must be atomic")
   x[!is.na(x)] 
}


    MANUAL <- quote(x[!is.na(x)])
    F.NOCHECK <-  quote(removeNA(x))
    F.CHECK <-  quote(removeNA.withCheck(x))

    mbench(MANUAL, F.NOCHECK, F.CHECK, checkEQUAL=TRUE)


  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 
          RESULTS:
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 
 Unit: milliseconds            Number of Repetitions: 200
        expr      min       lq   median       uq      max
    MANUAL : 25.00522 27.33629 29.86619 35.83740 139.1318
 F.NOCHECK : 24.85922 27.41522 30.84681 36.29844  56.0852
   F.CHECK : 24.90629 26.12730 29.97504 34.24987 129.8002