# rowIQRs: Estimates of the interquartile range for each row (column) in... In matrixStats: Functions that Apply to Rows and Columns of Matrices (and to Vectors)

## Description

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

## Usage

 ```1 2 3 4 5``` ```rowIQRs(x, rows = NULL, cols = NULL, na.rm = FALSE, ...) colIQRs(x, rows = NULL, cols = NULL, na.rm = FALSE, ...) iqr(x, idxs = NULL, na.rm = FALSE, ...) ```

## Arguments

 `x` A `numeric` NxK `matrix`. `na.rm` If `TRUE`, missing values are dropped first, otherwise not. `...` Additional arguments passed to `rowQuantiles`() (`colQuantiles()`). `idxs, rows, cols` A `vector` indicating subset of elements (or rows and/or columns) 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_.

## Author(s)

Henrik Bengtsson

See `IQR`. See `rowSds`().

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16``` ```set.seed(1) x <- matrix(rnorm(50 * 40), nrow = 50, ncol = 40) str(x) # Row IQRs q <- rowIQRs(x) print(q) q0 <- apply(x, MARGIN = 1, FUN = IQR) stopifnot(all.equal(q0, q)) # Column IQRs q <- colIQRs(x) print(q) q0 <- apply(x, MARGIN = 2, FUN = IQR) stopifnot(all.equal(q0, q)) ```

### Example output

``` num [1:50, 1:40] -0.626 0.184 -0.836 1.595 0.33 ...
[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
[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
```

matrixStats documentation built on Feb. 11, 2018, 3:12 p.m.