This program performs a Trend Surface Analysis
(Borcard et al. 2011, Legendre and Legendre 2012, Lichstein et al 2002)
for the data Z and the given coordinates, projected or in decimal degrees format,
in which case will be projected with geoXY.
eco.detrend(Z, XY, degree, center = TRUE, scale = FALSE, raw = FALSE, latlon = FALSE)
| Z | Data frame, matrix or vector with dependent variables. |
|---|---|
| XY | Data frame, matrix or vector with projected coordinates (X, XY or XYZ). For longitude-latitude data in decimal degrees format, use the option latlon = TRUE. |
| degree | Polynomial degree. |
| center | Should the data be centered? Default TRUE |
| scale | Should the data be scaled? Default FALSE |
| raw | Use raw and not orthogonal polynomials? Default FALSE |
| latlon | Are the coordinates in decimal degrees format? Defalut FALSE. If TRUE,
the coordinates must be in a data.frame/matrix with the longitude in the first
column and latitude in the second. The position is projected onto a plane in
meters with the function |
An object of class "eco.detrend" with the following slots:
> POLY.DEG polynomial degree used in the analysis
> RES detrended data
> XY projected coordinates
> MODEL models selected with the Akaike criterion
> ANALYSIS object of class "eco.mlm" with the regression results for each variable
ACCESS TO THE SLOTS The content of the slots can be accessed with the corresponding accessors, using the generic notation of EcoGenetics (<ecoslot.> + <name of the slot> + <name of the object>). See help("EcoGenetics accessors") and the Examples section below.
Borcard D., F. Gillet, and P. Legendre. 2011. Numerical ecology with R. Springer Science & Business Media.
Legendre P., and L. Legendre. 2012. Numerical ecology. Third English edition. Elsevier Science, Amsterdam, Netherlands.
Lichstein J., T. Simons, S. Shriner, and K. Franzreb. 2002. Spatial autocorrelation and autoregressive models in ecology. Ecological monographs, 72: 445-463.
# NOT RUN { data(eco2) # original data data1 <- matrix(eco2[["P"]][,1], 30, 30) image(data1) # original data + trend data2 <- matrix(eco2[["P"]][,2], 30, 30) image(data2) # data detrending data2.det <- eco.detrend(Z = eco2[["P"]][,2], XY = eco2[["XY"]], degree = 1) #----------------------- # ACCESSORS USE EXAMPLE #----------------------- # the slots are accesed with the generic format # (ecoslot. + name of the slot + name of the object). # See help("EcoGenetics accessors") data2.det <- ecoslot.RES(data2.det) # detrended data in slot RES data2.det <- matrix(data2.det[,1], 30, 30) image(data2.det) # }