Plot "biplot" for different decomposition methods.

The final graph shows the data points projected onto the first two components, together with the loadings as axes.

plot_biplot(obj, X = NULL, method = "pca", edges = NULL)

Arguments

obj

The output from comp_tsout_ens or mv_tsout_ens functions.

X

The data matrix used as input to mv_tsout_ens (not needed if obj is output from comp_tsout_ens).

method

The decomposition method, choose between "pca" (default), "dobin", "ics" or "ica".

edges

Set to "all" to connect points by time index, "outlying" to connect tagged outliers to previous and following points.

Value

A ggplot showing the biplot.

Examples

if (FALSE) {
set.seed(100)
n <- 600
x <- sample(1:100, n, replace=TRUE)
x[25] <- 200
x[320] <- 300
x2 <- sample(1:100, n, replace=TRUE)
x3 <- sample(1:100, n, replace=TRUE)
x4 <- sample(1:100, n, replace=TRUE)
X <- cbind.data.frame(x, x2, x3, x4)

out1 <- mv_tsout_ens(X, compr=2, fast=FALSE)
plot_biplot(out1, X = X, method = "pca")

X <- X/rowSums(X)
out2 <- comp_tsout_ens(X, compr=2, fast=FALSE)
plot_biplot(out2)
}