PlotNormTest (version 1.0.1)

get_params: 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)

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 called mt3_covTtTs(), or mt4_covTtTs().

• l.sTtTs Covariance matrix of linear combination of distinct derivatives, the function called mt3_covLtLs(), or mt4_covLtLs().

• m.supLT The Monte Carlo estimate of expected value supremum of the Gaussian process, see covLtLs().

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.

Arguments

p

Dimension.

bigt

Array containing value of \(t^*\).

l

Linear transformation of vector of third/fourth distinct derivatives, default is their average.

See Also

covZtZs(), covLtLs(), covTtTs()

Examples

# \donttest{
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)
# }