colMedians {robustbase} | R Documentation

## Fast Row or Column-wise Medians of a Matrix

### Description

Calculates the median for each row (column) of a matrix `x`. This is the same as but more efficient than `apply(x, MM, median)` for MM=2 or MM=1, respectively.

### Usage

    colMedians(x, na.rm = FALSE, hasNA = TRUE, keep.names=TRUE)
    rowMedians(x, na.rm = FALSE, hasNA = TRUE, keep.names=TRUE)

### Arguments

`x` | a `numeric` n x p `matrix`.
`na.rm` | if `TRUE`, `NA`s are excluded first, otherwise not.
`hasNA` | logical indicating if `x` may contain `NA`s. If set to `FALSE`, no internal NA handling is performed which typically is faster.
`keep.names` | logical indicating if row or column names of `x` should become `names` of the result - as is the case for `apply(x, MM, median)`.

### Details

The implementation of `rowMedians()` and `colMedians()` is optimized for both speed and memory. To avoid coercing to `double`s (and hence memory allocation), there is a special implementation for `integer` matrices. That is, if `x` is an `integer` `matrix`, then `rowMedians(as.double(x))` (`rowMedians(as.double(x))`) would require three times the memory of `rowMedians(x)` (`colMedians(x)`), but all this is avoided.

### Value

a `numeric` vector of length n or p, respectively.

### Missing values

Missing values are excluded before calculating the medians unless `hasNA` is false. Note that `na.rm` has no effect and is automatically false when `hasNA` is false, i.e., internally, before computations start, the following is executed:

    if (!hasNA)        ## If there are no NAs, don't try to remove them
         narm <- FALSE

### Author(s)

Henrik Bengtsson, Harris Jaffee, Martin Maechler

### See Also

See `wgt.himedian()` for a weighted hi-median, and `colWeightedMedians()` etc from package matrixStats for weighted medians.
For mean estimates, see `rowMeans()` in `colSums`().

### Examples

    set.seed(1); n <- 234; p <- 543 # n*p = 127'062
    x <- matrix(rnorm(n*p), n, p)
    x[sample(seq_along(x), size= n*p / 256)] <- NA
    R1 <- system.time(r1 <- rowMedians(x, na.rm=TRUE))
    C1 <- system.time(y1 <- colMedians(x, na.rm=TRUE))
    R2 <- system.time(r2 <- apply(x, 1, median, na.rm=TRUE))
    C2 <- system.time(y2 <- apply(x, 2, median, na.rm=TRUE))
    R2 / R1 # speedup factor: ~= 4   {platform dependent}
    C2 / C1 # speedup factor: ~= 5.8 {platform dependent}
    stopifnot(all.equal(y1, y2, tol=1e-15),
              all.equal(r1, r2, tol=1e-15))

    (m <- cbind(x1=3, x2=c(4:1, 3:4,4)))
    stopifnot(colMedians(m) == 3,
              all.equal(colMeans(m), colMedians(m)),# <- including names !
              all.equal(rowMeans(m), rowMedians(m)))

[Package robustbase version 0.93-4 Index]