## S3 method for class 'pca':
plot(x, ax = 1, ay = 2, col = 1, title = "", pch = 1, \dots)
## S3 method for class 'pca':
points(x, which, ax = 1, ay = 2, col = 2, pch = 1, cex = 1, \dots)
## S3 method for class 'pca':
plotid(ord, ids = seq(1:nrow(ord$scores)), ax = 1, ay = 2,
col = 1, ...)
## S3 method for class 'pca':
hilight(ord, overlay, ax = 1, ay = 2, cols=c(2,3,4,5,6,7), glyph=c(1,3,5),
origpch = 1, blank = '#FFFFFF', ...)
## S3 method for class 'pca':
chullord(ord, overlay, ax = 1, ay = 2, cols=c(2,3,4,5,6,7), ltys = c(1,2,3), ...)
## S3 method for class 'pca':
surf(ord, var, ax = 1, ay = 2, col = 2, labcex = 0.8,
family = gaussian, thinplate=TRUE, grid=50, gamma=1, \dots)
## S3 method for class 'pca':
varplot(x, dim=length(x$sdev))gamFunction
Function
Function
Function
Function
Function gam
function to fit a variable to the ordination coordinates, and to predict the
values at all grid points. The grid is established with the
data(bryceveg)
data(brycesite)
pca.1 <- pca(bryceveg)
plot(pca.1)
points(pca.1,brycesite$elev>8000)
surf(pca.1,brycesite$elev)
plotid(pca.1,ids=row.names(bryceveg))Run the code above in your browser using DataLab