# raster.deviation

0th

Percentile

##### Raster local deviation from the global trend

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

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 evaluate the local deviation from the global statistic [stat(x) - y-hat] where; stat(x) is the global value of the specified statistic and y-hat is the specified focal statistic.

##### Usage
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

##### 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

##### Aliases
• raster.deviation
##### Examples
# NOT RUN {
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")
par(opar)

# }

Documentation reproduced from package spatialEco, version 1.3-2, License: GPL-3

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