simulation {BinNor}

Repeats the data generation process in a simulation scheme

Description

Simulates many versions of mixed data, and reports averaged proportion, mean, variance and correlation estimates across replications.

Usage

simulation(seed = NULL, nsim, no.rows, no.bin, no.nor, 
	mean.vec.nor = NULL, var.nor = NULL, prop.vec.bin = NULL, 
	corr.vec = NULL, corr.mat = NULL, continue.with.warning = TRUE)

Arguments

seed

A seed value for the random number generator. Seed value will be randomly generated unless specified.

nsim

Number of simulation runs.

no.rows

Number of rows.

no.bin

Number of binary variables

no.nor

Number of normal variables

prop.vec.bin

Probability vector for binary variables

mean.vec.nor

Vector of means for normal variables

var.nor

Vector of variances for normal variables

corr.vec

Vector of elements below the diagonal of correlation matrix ordered columnwise

corr.mat

Specified correlation matrix

continue.with.warning

TRUE to proceed with the nearest positive definite \Sigma^*. FALSE to terminate program execution if \Sigma^* is not positive definite

See Also

compute.sigma.star, jointly.generate.binary.normal

Examples

simulation(nsim=10, no.rows=100, no.bin=2, no.nor=2, 
		mean.vec.nor=c(3,1), var.nor=c(4,2), prop.vec.bin=c(0.4,0.7),
		corr.vec=c(0.16,0.04,0.38,0.14,0.47,0.68), corr.mat=NULL)