validation.skewness.kurtosis {BinNonNor} | R Documentation |
Validates the marginal specification of the continuous non-normal variables
Description
Checks whether the marginal specification of the continuous non-normal part is valid and consistent.
Usage
validation.skewness.kurtosis(n.NN, skewness.vec = NULL, kurtosis.vec = NULL)
Arguments
n.NN |
Number of continuous non-normal variables. |
skewness.vec |
Skewness vector for continuous non-normal variables. |
kurtosis.vec |
Kurtosis vector for continuous non-normal 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.NN<-3
skewness.vec=c(0,2,3)
kurtosis.vec=c(-1.2,6,8)
validation.skewness.kurtosis(n.NN,skewness.vec,kurtosis.vec)
## Not run:
n.NN<--1
skewness.vec=c(0)
kurtosis.vec=c(-1.2)
validation.skewness.kurtosis(n.NN,skewness.vec,kurtosis.vec)
n.NN<-3
skewness.vec=c(0,2,3)
kurtosis.vec=c(-1.2,6,5)
validation.skewness.kurtosis(3)
n.NN<-3
skewness.vec=c(0,2,3)
kurtosis.vec=c(-1.2,6,5)
validation.skewness.kurtosis(n.NN,skewness.vec)
validation.skewness.kurtosis(n.NN,kurtosis.vec)
n.NN<-0
skewness.vec=c(0,2,3)
kurtosis.vec=c(-1.2,6,8)
validation.skewness.kurtosis(n.NN,skewness.vec,kurtosis.vec)
n.NN<-2
skewness.vec=c(0,2,3)
kurtosis.vec=c(-1.2,6,8)
validation.skewness.kurtosis(n.NN,skewness.vec,kurtosis.vec)
n.NN<-2
skewness.vec=c(0,2,3)
kurtosis.vec=c(-1.2,6)
validation.skewness.kurtosis(n.NN,skewness.vec,kurtosis.vec)
skewness.vec=c(2,3)
kurtosis.vec=c(1,5)
validation.skewness.kurtosis(n.NN,skewness.vec,kurtosis.vec)
## End(Not run)
[Package BinNonNor version 1.5.3 Index]