# raster.deviation: Raster local deviation from the global trend In jeffreyevans/spatialEco: Spatial Analysis and Modelling Utilities

## Description

Calculates the local deviation from the raster, a specified global statistic or a polynomial trend of the raster.

## Usage

 `1` ```raster.deviation(x, type = "trend", s = 3, degree = 1, global = FALSE) ```

## Arguments

 `x` raster object `type` The global statistic to represent the local deviation options are: "trend", "min", "max", "mean", "median" `s` Size of matrix (focal window), not used with type="trend" `degree` The polynomial degree if type is trend, options are 1 and 2. `global` Use single global value for deviation or cell-level values (FALSE/TRUE). Argument is ignored for type="trend"

## Value

raster class object of the local deviation from the raster or specified global statistic

## Note

The deviation from the trend is derived as [y-hat - y] where; y-hat is the Nth-order polynomial. Whereas the deviation from a global statistic is [y - y-hat] where; y-hat is the local (focal) statistic. The global = TRUE argument allows one to evalute the local deviation from the global statistic [stat(x) - y-hat] where; stat(x) is the global value of the specified staistic and y-hat is the specified focal statistic.

## Author(s)

Jeffrey S. Evans <[email protected]>

## References

Magee, Lonnie (1998). Nonlocal Behavior in Polynomial Regressions. The American Statistician. American Statistical Association. 52(1):20-22 Fan, J. (1996). Local Polynomial Modelling and Its Applications: From linear regression to nonlinear regression. Monographs on Statistics and Applied Probability. Chapman and Hall/CRC. ISBN 0-412-98321-4

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13``` ``` library(raster) data(elev) # local deviation from first-order trend, global mean and raw value r.dev.trend <- raster.deviation(elev, type="trend", degree=1) r.dev.mean <- raster.deviation(elev, type="mean", s=5) r.gdev.mean <- raster.deviation(elev, type="mean", s=5, global=TRUE) par(mfrow=c(2,2)) plot(elev, main="original") plot(r.dev.trend, main="dev from trend") plot(r.dev.mean, main="dev of mean from raw values") plot(r.gdev.mean, main="local dev from global mean") ```

jeffreyevans/spatialEco documentation built on Jan. 15, 2019, 11:15 a.m.