# layerStats

##### Correlation and (weighted) covariance

Compute correlation and (weighted) covariance for multi-layer Raster objects. Like `cellStats`

this function returns a few values, not a Raster* object (see `Summary-methods`

for that).

##### Usage

`layerStats(x, stat, w, asSample=TRUE, na.rm=FALSE, ...)`

##### Arguments

- x
RasterStack or RasterBrick for which to compute a statistic

- stat
Character. The statistic to compute: either 'cov' (covariance), 'weighted.cov' (weighted covariance), or 'pearson' (correlation coefficient)

- w
RasterLayer with the weights (should have the same extent, resolution and number of layers as

`x`

) to compute the weighted covariance- asSample
Logical. If

`TRUE`

, the statistic for a sample (denominator is`n-1`

) is computed, rather than for the population (denominator is`n`

)- na.rm
Logical. Should missing values be removed?

- ...
Additional arguments (none implemetned)

##### Value

List with two items: the correlation or (weighted) covariance matrix, and the (weighted) means.

##### References

For the weighted covariance:

Canty, M.J. and A.A. Nielsen, 2008. Automatic radiometric normalization of multitemporal satellite imagery with the iteratively re-weighted MAD transformation. Remote Sensing of Environment 112:1025-1036.

Nielsen, A.A., 2007. The regularized iteratively reweighted MAD method for change detection in multi- and hyperspectral data. IEEE Transactions on Image Processing 16(2):463-478.

##### See Also

##### Examples

```
# NOT RUN {
b <- brick(system.file("external/rlogo.grd", package="raster"))
layerStats(b, 'pearson')
layerStats(b, 'cov')
# weigh by column number
w <- init(b, v='col')
layerStats(b, 'weighted.cov', w=w)
# }
```

*Documentation reproduced from package raster, version 2.9-5, License: GPL (>= 3)*