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raster (version 2.6-7)

# cellStats: Statistics across cells

## Description

Compute statistics for the cells of each layer of a Raster* object. In the `raster` package, functions such as max, min, and mean, when used with Raster* objects as argument, return a new Raster* object (with a value computed for each cell). In contrast, cellStats returns a single value, computed from the all the values of a layer. Also see `layerStats`

## Usage

```# S4 method for RasterLayer
cellStats(x, stat='mean', na.rm=TRUE, asSample=TRUE, ...)# S4 method for RasterStackBrick
cellStats(x, stat='mean', na.rm=TRUE, asSample=TRUE, ...)```

## Arguments

x

Raster* object

stat

The function to be applied. See Details

na.rm

Logical. Should `NA` values be removed?

asSample

Logical. Only relevant for `stat=sd` in which case, if `TRUE`, the standard deviation for a sample (denominator is `n-1`) is computed, rather than for the population (denominator is `n`)

...

Numeric

## Details

`cellStats` will fail (gracefully) for very large Raster* objects except for a number of known functions: sum, mean, min, max, sd, 'skew' and 'rms'. 'skew' (skewness) and 'rms' (Root Mean Square) must be supplied as a character value (with quotes), the other known functions may be supplied with or without quotes. For other functions you could perhaps use a sample of the RasterLayer that can be held in memory (see `sampleRegular` )

`freq`, `quantile`, `minValue`, `maxValue`, `setMinMax`

## Examples

Run this code
``````# NOT RUN {
r <- raster(nrow=18, ncol=36)
r[] <- runif(ncell(r)) * 10
# works for large files
cellStats(r, 'mean')
# same, but does not work for very large files
cellStats(r, mean)
# multi-layer object
cellStats(brick(r,r), mean)
# }
``````

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