miscor (version 0.1-0)

sim.cor: Simulate bivariate distribution with a specified correlation

Description

This function simulates bivariate distribution with correaltion equal to rho, mean equal to mean, standard deviation equal to sd, skewness equal to skewness, and kurtosis equal to kurtosis by Fleishman polynomials.

Usage

sim.cor(n, rho, mean = c(0, 0), sd = c(1, 1), skewness = c(0, 0), kurtosis = c(0, 0))

Arguments

n

number of observations.

rho

correlation.

mean

mean vector.

sd

standard deviation vector.

skewness

skewness vector.

kurtosis

kurtosis vector.

Value

Returns a data.frame with variables x and y.

References

Rasch, D., Kubinger, K. D., & Yanagida, T. (2011). Statistics in psychology - Using R and SPSS. New York: John Wiley & Sons.

See Also

test.cor, seqtest.cor, comptest.cor,

Examples

#------------------------------------------------
# Bivariate  distribution with rho = 0.3, n = 200
# x: skewness = 0, kurtosis = 0
# y: skewness = 0, kurtosis = 0

sim.cor(200, rho = 0.3)

#-----------------------------------------------
# Bivariate distribution with rho = 0.4, n = 500
# x: skewness = 0, kurtosis = 1.5
# y: skewness = 2, kurtosis = 7

sim.cor(500, rho = 0.4, skewness = c(0, 1.5), kurtosis = c(2, 7))