plot_cov function

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

Returns

A covariance plot

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)

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.