Show and Interpolate Two Dimensional Distribution of Residuals
residualssurface(model, data, x, y, gam = F, npol = 2, plotit = T, filled = F, bubble = F)
model |
|
data |
Data set that contains the spatial coordinates of the sample units used for the original model (specified as "x" and "y"). |
x |
Horizontal position of the sample units. |
y |
Vertical position of the sample units. |
gam |
Interpolate the spatial structure by |
npol |
Degree of polynomial surface as passed to |
plotit |
Plot the interpolated surface (through |
filled |
Fill the contours by |
bubble |
Provide a bubble graph of the residuals: circles indicate positive residuals, whereas squares indicate negative residuals. |
The function reports the results of a GAM or least-squares trend surface analysis of the spatial distribution of residuals of a model (through residuals
).
Optionally, a graph is produced that can contain the trend surface, filled contours and bubble graphs in addition to the spatial location of the sample units.
The function reports the results of a GAM or least-squares trend surface analysis of the spatial distribution of residuals. Optionally, a graph is provided.
Roeland Kindt (World Agroforestry Centre)
Kindt, R. & Coe, R. (2005) Tree diversity analysis: A manual and software for common statistical methods for ecological and biodiversity studies.
library(vegan) library(mgcv) library(akima) data(faramea) Count.model1 <- lm(Faramea.occidentalis ~ Precipitation, data=faramea, na.action=na.exclude) surface.1 <- residualssurface(Count.model1, na.omit(faramea), 'UTM.EW', 'UTM.NS', gam=TRUE, plotit=TRUE, bubble=TRUE)
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