Plotting Covariance Matrix

Plotting Covariance Matrix

plot_cov(sobj, type = "relpos", ordering = TRUE, facetting = TRUE)

Arguments

sobj	A simrel object
type	Type of covariance matrix - can take two values relpos for relevant position of principal components and relpred for relevant position of predictor variables
ordering	TRUE for ordering the covariance for block diagonal display
facetting	TRUE for facetting the predictor and response space. FALSE will give a single facet plot

Value

A covariance plot

References

Sæbø, S., Almøy, T., & Helland, I. S. (2015). simrel—A versatile tool for linear model data simulation based on the concept of a relevant subspace and relevant predictors. Chemometrics and Intelligent Laboratory Systems, 146, 128-135.

Almøy, T. (1996). A simulation study on comparison of prediction methods when only a few components are relevant. Computational statistics & data analysis, 21(1), 87-107.

Rimal, R., Almøy, T., & Sæbø, S. (2018). A tool for simulating multi-response linear model data. Chemometrics and Intelligent Laboratory Systems, 176, 1-10.

Examples

sobj <- simrel(n = 100, p = 10, q = c(4, 5), relpos = list(c(1, 2, 3), c(4, 6, 7)), m = 3,
               R2 = c(0.8, 0.7), ypos = list(c(1, 3), 2), gamma = 0.7, type = "multivariate")
p1 <- plot_cov(sobj, type = "relpos", facetting = FALSE)
p2 <- plot_cov(sobj, type = "rotation", facetting = FALSE)
p3 <- plot_cov(sobj, type = "relpred", facetting = FALSE)
gridExtra::grid.arrange(p1, p2, p3, ncol = 3)