get_params {PlotNormTest} | R Documentation |
Get parameters for plots derivatives of multivariate CGF to assess normality assumption.
Description
Obtain necessary parameters to build a graphical test using the third/fourth derivatives of cumulant generating function.
Usage
mt3_get_param(p, bigt = seq(-1, 1, by = 0.05)/sqrt(p), l = NULL)
mt4_get_param(p, bigt = seq(-1, 1, by = 0.05)/sqrt(p), l = NULL)
Arguments
p |
Dimension. |
bigt |
Array containing value of |
l |
Linear transformation of vector of third/fourth distinct derivatives, default is their average. |
Value
p
Dimension.lT
Number of distinct third/fourth order derivatives.sTtTs
Two dimensional array, each element contains covariance matrix of vector of derivatives, the function calledmt3_covTtTs()
, ormt4_covTtTs()
.l.sTtTs
Covariance matrix of linear combination of distinct derivatives, the function calledmt3_covLtLs()
, ormt4_covLtLs()
.m.supLT
The Monte Carlo estimate of expected value supremum of the Gaussian process, seecovLtLs()
.
mt3_get_param
returns necessary parameters for the 2D plot
relying on third derivatives.
mt4_get_param
returns necessary parameters for the 2D plot
relying on fourth derivatives.
See Also
covZtZs()
,
covLtLs()
, covTtTs()
Examples
p <- 2
mt3 <- mt3_get_param(p, bigt = seq(-1, 1, .5)/sqrt(p))
names(mt3)
mt4 <- mt4_get_param(p, bigt = seq(-1, 1, .5)/sqrt(p))
names(mt4)