Multivariate_CGF_PLot {PlotNormTest} | R Documentation |
Graphical plots to assess multivariate normality assumption.
Description
Cumulant generating functions of normally distributed
random variables has derivatives of order higher than 3 are all 0.
Hence, plots of empirical third/fourth order derivatives with large value
or high slope gives indication of non-normality.
Multivariate_CGF_PLot
estimates and provides confidence region for
average (or any linear combination) of third/fourth derivatives of empirical
cumulant function at the points t = t^*1_p
. Plots for
p = 2, 3, \dots, 10
will be faster to obtain, as confidence regions
and other necessary parameters are available in mt3_lst_param.rda
and
mt4_lst_param.rda
.
Higher dimension requires expensive computational cost.
Usage
d3hCGF_plot(x, alpha = 0.05)
d4hCGF_plot(x, alpha = 0.05)
Arguments
x |
Data matrix of size |
alpha |
Significant level (default is |
Value
d3hCGF_plot
returns plot relying in third derivatives.
d4hCGF_plot
returns plot relying in forth derivatives.
See Also
Examples
set.seed(1234)
p <- 3
x <- MASS::mvrnorm(500, rep(0, p), diag(p))
d3hCGF_plot(x)
d4hCGF_plot(x)