Calculates the median for each row in a matrix

Description

Calculates the median for each row in a matrix.

Usage

## S3 method for class 'matrix':
rowMedians(x, na.rm=FALSE, ...)

Arguments

Details

The main difference between this implementation and the one in Biobase, rowMedians, is that this one handles missing values too. This implementation is also optimized for speed and memory to calculate the median value whereas the Biobase version uses a more generic method to estimate and quantiles, cf. rowQ.

Value

Returns a double vector of length equal to number of rows in x.

Benchmarking

As the example shows, this implementation is roughly 3-10 times faster than using apply(x, MARGIN=1, FUN=medians) (as of R v2.4.0).

Author(s)

Henrik Bengtsson (http://www.braju.com/R/)

See Also

See rowMeans() in colSums().

Examples

# - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Consistency checks
# - - - - - - - - - - - - - - - - - - - - - - - - - - - -
cat("Consistency checks:\n")
for (kk in 1:20) {
  cat("Random test #", kk, "\n", sep="")

  # Simulate data in a matrix of any shape
  nrow <- sample(2000, size=1)
  ncol <- sample(2000, size=1)
  x <- rnorm(nrow*ncol)
  dim(x) <- c(nrow, ncol)

  # Add NAs?
  nas <- sample(c(TRUE,FALSE), size=1)
  if (nas) {
    nna <- sample(nrow*ncol, size=1)
    x[sample(length(x), size=nna)] <- NA
  }

  na.rm <- sample(c(TRUE,FALSE), size=1)
  t1 <- system.time({
    y1 <- rowMedians(x, na.rm=na.rm)
  })
  t2 <- system.time({
    y2 <- apply(x, MARGIN=1, FUN=median, na.rm=na.rm)
  })
  # When all values of 'y2' are NA, 'y2' is logical
  if (is.logical(y2)) y2 <- as.double(y2)
  stopifnot(identical(y1,y2))
  cat(sprintf("rowMedians()/apply(): %.3g\n", (t1/t2)[3]))
}