validation.skewness.kurtosis: Validates the marginal specification of the continuous...

In PoisBinNonNor: Data Generation with Poisson, Binary and Continuous Components

Description

Checks whether the marginal specification of the continuous part is valid and consistent.

Usage

validation.skewness.kurtosis(n.C, skewness.vec = NULL, kurtosis.vec = NULL)

Arguments

n.C	Number of continuous variables.
skewness.vec	Skewness vector for continuous variables.
kurtosis.vec	Kurtosis vector for continuous variables.

Value

The function returns TRUE if no specification problem is encountered. Otherwise, it returns an error message.

References

Demirtas, H., Hedeker, D., and Mermelstein, R.J. (2012). Simulation of massive public health data by power polynomials. Statistics in Medicine, 31(27), 3337-3346.

Examples

n.C<-3
skewness.vec=c(0,2,3)
kurtosis.vec=c(-1.2,6,8)
validation.skewness.kurtosis(n.C,skewness.vec,kurtosis.vec)

## Not run: 
n.C<--1
skewness.vec=c(0)
kurtosis.vec=c(-1.2)
validation.skewness.kurtosis(n.C,skewness.vec,kurtosis.vec)

n.C<-3
skewness.vec=c(0,2,3)
kurtosis.vec=c(-1.2,6,5)
validation.skewness.kurtosis(3)

n.C<-3
skewness.vec=c(0,2,3)
kurtosis.vec=c(-1.2,6,5)
validation.skewness.kurtosis(n.C,skewness.vec)
validation.skewness.kurtosis(n.C,kurtosis.vec)

n.C<-0
skewness.vec=c(0,2,3)
kurtosis.vec=c(-1.2,6,8)
validation.skewness.kurtosis(n.C,skewness.vec,kurtosis.vec)

n.C<-2
skewness.vec=c(0,2,3)
kurtosis.vec=c(-1.2,6,8)
validation.skewness.kurtosis(n.C,skewness.vec,kurtosis.vec)

n.C<-2
skewness.vec=c(0,2,3)
kurtosis.vec=c(-1.2,6)
validation.skewness.kurtosis(n.C,skewness.vec,kurtosis.vec)

skewness.vec=c(2,3)
kurtosis.vec=c(1,5)
validation.skewness.kurtosis(n.C,skewness.vec,kurtosis.vec)

## End(Not run)

PoisBinNonNor documentation built on March 22, 2021, 9:07 a.m.