raster.kendall: Kendall tau trend with continuity correction for raster...

In spatialEco: Spatial Analysis and Modelling Utilities

Kendall tau trend with continuity correction for raster time-series

Description

Calculates a nonparametric statistic for a monotonic trend based on the Kendall tau statistic and the Theil-Sen slope modification

Usage

raster.kendall(
  x,
  intercept = TRUE,
  p.value = TRUE,
  confidence = TRUE,
  tau = TRUE,
  min.obs = 6,
  method = c("zhang", "yuepilon", "none"),
  ...
)

Arguments

x	A multiband terra SpatRaster object with at least 5 layers
intercept	(FALSE/TRUE) return a raster with the pixel wise intercept values
p.value	(FALSE/TRUE) return a raster with the pixel wise p.values
confidence	(FALSE/TRUE) return a raster with the pixel wise 95 pct confidence levels
tau	(FALSE/TRUE) return a raster with the pixel wise tau correlation values
min.obs	The threshold of minimum number of observations (default 6)
method	Kendall method to use c("zhang", "yuepilon","none"), see kendall function
...	Additional arguments passed to the terra app function

Details

This function implements Kendall's nonparametric test for a monotonic trend using the Theil-Sen (Theil 1950; Sen 1968; Siegel 1982) method to estimate the slope and related confidence intervals.

Value

Depending on arguments, a raster layer or rasterBrick object containing:

• raster layer 1 - slope for trend, always returned

• raster layer 2 - Kendall's tau two-sided test, reject null at 0, if tau TRUE

• raster layer 3 - intercept for trend if intercept TRUE

• raster layer 4 - p value for trend fit if p.value TRUE

• raster layer 5 - lower confidence level at 95 pct, if confidence TRUE

• raster layer 6 - upper confidence level at 95 pct, if confidence TRUE

Author(s)

Jeffrey S. Evans [e-mail]

References

Theil, H. (1950) A rank invariant method for linear and polynomial regression analysis. Nederl. Akad. Wetensch. Proc. Ser. A 53:386-392 (Part I), 53:521-525 (Part II), 53:1397-1412 (Part III).

Sen, P.K. (1968) Estimates of Regression Coefficient Based on Kendall's tau. Journal of the American Statistical Association. 63(324):1379-1389.

Siegel, A.F. (1982) Robust Regression Using Repeated Medians. Biometrika, 69(1):242-244

See Also

zyp.trend.vector for model details

app for available ... arguments

Examples

 library(terra)

 # note; nonsense example with n=9
 r <- c(rast(system.file("ex/logo.tif", package="terra")),
        rast(system.file("ex/logo.tif", package="terra")),
        rast(system.file("ex/logo.tif", package="terra"))) 
 
 # Calculate trend slope with p-value and confidence level(s)
 # ("slope","intercept", "p.value","z.value", "LCI","UCI","tau")
   k <- raster.kendall(r, method="none")
   plot(k)

spatialEco documentation built on Nov. 18, 2023, 1:13 a.m.