colWeightedMedians {DelayedMatrixStats} | R Documentation

## Calculates the weighted medians for each row (column) in a matrix

### Description

Calculates the weighted medians for each row (column) in a matrix.

### Usage

    colWeightedMedians(x, w = NULL, rows = NULL, cols = NULL, na.rm = FALSE,
      ...)

    rowWeightedMedians(x, w = NULL, rows = NULL, cols = NULL, na.rm = FALSE,
      ...)

    ## S4 method for signature 'DelayedMatrix'
    colWeightedMedians(x, w = NULL, rows = NULL,
      cols = NULL, na.rm = FALSE, force_block_processing = FALSE, ...)

    ## S4 method for signature 'DelayedMatrix'
    rowWeightedMedians(x, w = NULL, rows = NULL,
      cols = NULL, na.rm = FALSE, force_block_processing = FALSE, ...)

### Arguments

`x` | A NxK DelayedMatrix.
`w` | A `numeric` `vector` of length K (N).
`rows` | A `vector` indicating subset of rows (and/or columns) to operate over. If `NULL`, no subsetting is done.
`cols` | A `vector` indicating subset of rows (and/or columns) to operate over. If `NULL`, no subsetting is done.
`na.rm` | If `TRUE`, missing values are excluded from the calculation, otherwise not.
`...` | Additional arguments passed to specific methods.
`force_block_processing` | `FALSE` (the default) means that a seed-aware, optimised method is used (if available). This can be overridden to use the general block-processing strategy by setting this to `TRUE` (typically not advised). The block-processing strategy loads one or more (depending on `getOption("DelayedArray.block.size")`) columns (`colFoo()`) or rows (`rowFoo()`) into memory as an ordinary base::array.

### Details

The implementations of these methods are optimized for both speed and memory. If no weights are given, the corresponding `rowMedians`()/`colMedians()` is used.

### Value

Returns a `numeric` `vector` of length N (K).

### See Also

Internally, `weightedMedian`() is used. See `rowMedians`() and `colMedians()` for non-weighted medians.

### Examples

    # A DelayedMatrix with a 'SolidRleArraySeed' seed
    dm_Rle <- RleArray(Rle(c(rep(1L, 5),
                             as.integer((0:4) ^ 2),
                             seq(-5L, -1L, 1L))),
                       dim = c(5, 3))

    # Specifying weights inversely proportional to rowwise MADs
    colWeightedMedians(dm_Rle, w = 1 / rowMads(dm_Rle))

[Package DelayedMatrixStats version 1.0.3 Index]