Estimates of the interquartile range for each row (column) in a matrix

Estimates of the interquartile range for each row (column) in a matrix.

rowIQRs(x, rows = NULL, cols = NULL, na.rm = FALSE, ...,
  useNames = TRUE)

colIQRs(x, rows = NULL, cols = NULL, na.rm = FALSE, ...,
  useNames = TRUE)

iqr(x, idxs = NULL, na.rm = FALSE, ...)

Arguments

x

An NxK matrix or, if dim. is specified, an N * K vector.

rows

A vector indicating subset of rows to operate over. If NULL, no subsetting is done.

cols

A vector indicating subset of columns to operate over. If NULL, no subsetting is done.

na.rm

If TRUE, missing values are excluded.

...

Additional arguments passed to rowQuantiles() (colQuantiles()).

useNames

If TRUE (default), names attributes of the result are set, otherwise not.

idxs

A vector indicating subset of elements to operate over. If NULL, no subsetting is done.

Value

Returns a numeric vector of length N (K).

Missing values

Contrary to IQR, which gives an error if there are missing values and na.rm = FALSE, iqr() and its corresponding row and column-specific functions return NA_real_.

See also

See IQR. See rowSds().

Author

Henrik Bengtsson

Examples

set.seed(1)

x <- matrix(rnorm(50 * 40), nrow = 50, ncol = 40)
str(x)
#>  num [1:50, 1:40] -0.626 0.184 -0.836 1.595 0.33 ...

# Row IQRs
q <- rowIQRs(x)
print(q)
#>  [1] 1.1731306 1.0107162 1.6654064 1.2539423 1.3705467 1.6404858 1.6995732
#>  [8] 1.3291742 1.6886054 1.2549506 0.9359126 1.0195589 1.4007595 1.2198987
#> [15] 1.0787055 1.4524548 1.2556678 1.6562935 0.9436753 1.5332922 1.0804972
#> [22] 1.3345150 1.3778290 1.2813150 1.1560162 1.2670159 1.6274822 1.0123151
#> [29] 1.3011232 0.9232206 1.3664274 1.6141894 1.3007675 1.3635105 1.1991735
#> [36] 1.1799147 1.5664136 1.1915430 1.3908429 1.2292913 1.3337325 1.1083987
#> [43] 1.1150356 1.3610511 1.9523920 1.1711522 1.8068631 1.4450980 1.7511271
#> [50] 1.1295912
q0 <- apply(x, MARGIN = 1, FUN = IQR)
stopifnot(all.equal(q0, q))

# Column IQRs
q <- colIQRs(x)
print(q)
#>  [1] 1.100049 1.178648 0.916382 1.523818 1.233231 1.177970 1.248359 1.281653
#>  [9] 1.305779 1.463096 1.121270 1.524690 1.262950 1.608730 1.937564 1.666534
#> [17] 1.370162 1.238580 1.341196 1.214581 1.610758 1.488645 1.361843 1.332965
#> [25] 1.244894 1.507090 1.172773 1.349565 1.511738 1.213386 1.241099 1.408363
#> [33] 1.050347 1.389932 1.806088 1.377805 1.241565 1.241594 1.234828 1.580717
q0 <- apply(x, MARGIN = 2, FUN = IQR)
stopifnot(all.equal(q0, q))