plot_biplot: Plot "biplot" for different decomposition methods.

In composits: Compositional, Multivariate and Univariate Time Series Outlier Ensemble

Plot "biplot" for different decomposition methods.

Description

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

Usage

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

## Not run: 
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)

## End(Not run)

composits documentation built on May 25, 2022, 9:11 a.m.