two.b.pls(A1, A2, iter = 999, seed = NULL, print.progress = TRUE)
gpagen
]. If other variables are used, they must be input as a
2-Dimensional matrix (rows = specimens, columns = variables). It is also assumed that the separate inputs
have specimens (observations) in the same order.
The generic functions, print
, summary
, and plot
all work with two.b.pls
.
The generic function, plot
, produces a two-block.pls plot. This function calls plot.pls
, which has two additional
arguments (with defaults): label = NULL, warpgrids = TRUE. These arguments allow one to include a vector to label points and a logical statement to
include warpgrids, respectively. Warpgrids can only be included for 3D arrays of Procrustes residuals. The plot is a plot of PLS scores from
Block1 versus Block2 performed for the first set of PLS axes.
Notes for geomorph 3.0
There is a slight change in two.b.pls plots with geomorph 3.0. Rather than use the shapes of specimens that matched minimum and maximum PLS
scores, major-axis regression is used and the extreme fitted values are used to generate deformation grids. This ensures that shape deformations
are exactly along the major axis of shape covariation. This axis is also shown as a best-fit line in the plot.integration.test
, modularity.test
, phylo.pls
, and
phylo.integration
data(plethShapeFood)
Y.gpa<-gpagen(plethShapeFood$land) #GPA-alignment
#2B-PLS between head shape and food use data
PLS <-two.b.pls(Y.gpa$coords,plethShapeFood$food,iter=999)
summary(PLS)
plot(PLS)
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