sim.cor: Simulate bivariate distribution with a specified correlation

In miscor: Miscellaneous Functions for the Correlation Coefficient

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. Note that that the specified skewness and kurtosis parameters have to be in line with kurtosis >= (skewnewss^2 - 2)

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.

Author(s)

Takuya Yanagida [e-mail],

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))

miscor documentation built on May 1, 2019, 10:14 p.m.