Simulation Plot with ggplot: The true beta, relevant component and eigen structure

Simulation Plot with ggplot: The true beta, relevant component and eigen structure

ggsimrelplot(
  obj,
  ncomp = min(obj$p, obj$n, 20),
  which = 1L:3L,
  layout = NULL,
  print.cov = FALSE,
  use_population = TRUE
)

Arguments

obj	A simrel object
ncomp	Number of components to plot
which	A character indicating which plot you want as output, it can take TrueBeta, RelComp and EstRelComp
layout	A layout matrix of how to layout multiple plots
print.cov	Output estimated covariance structure
use_population	Logical, TRUE if population values should be used and FALSE if sample values should be used

Value

A list of plots

Examples

sim.obj <- simrel(n = 100, p = 16, q = c(3, 4, 5),
   relpos = list(c(1, 2), c(3, 4), c(5, 7)), m = 5,
   ypos = list(c(1, 4), 2, c(3, 5)), type = "multivariate",
   R2 = c(0.8, 0.7, 0.9), gamma = 0.8)

ggsimrelplot(sim.obj, layout = matrix(c(2, 1, 3, 1), 2))

ggsimrelplot(sim.obj, which = c(1, 2), use_population = TRUE)

ggsimrelplot(sim.obj, which = c(1, 2), use_population = FALSE)

ggsimrelplot(sim.obj, which = c(1, 3), layout = matrix(c(1, 2), 1))