fleish: Fleishman's Third-Order Polynomial Transformation Equations

In SimMultiCorrData: Simulation of Correlated Data with Multiple Variable Types

Description

This function contains Fleishman's third-order polynomial transformation equations (doi: 10.1007/BF02293811). It is used in find_constants to find the constants c1, c2, and c3 (c0 = -c2) that satisfy the equations given skewness and standardized kurtosis values. It can be used to verify a set of constants satisfy the equations. Note that there exist solutions that yield invalid power method pdfs (see power_norm_corr, pdf_check). This function would not ordinarily be called by the user.

Usage

fleish(c, a)

Arguments

c	a vector of constants c1, c2, c3; note that find_constants returns c0, c1, c2, c3
a	a vector c(skewness, standardized kurtosis)

Value

a list of length 3; if the constants satisfy the equations, returns 0 for all list elements

References

Fleishman AI (1978). A Method for Simulating Non-normal Distributions. Psychometrika, 43, 521-532. doi: 10.1007/BF02293811.

Headrick TC, Sawilowsky SS (1999). Simulating Correlated Non-normal Distributions: Extending the Fleishman Power Method. Psychometrika, 64, 25-35. doi: 10.1007/BF02294317.

See Also

poly, power_norm_corr, pdf_check, find_constants

Examples

# Laplace Distribution
fleish(c = c(0.782356, 0, 0.067905), a = c(0, 3))

Example output

Attaching package: 'SimMultiCorrData'

The following object is masked from 'package:stats':

    poly

[1] 2.551191e-06 0.000000e+00 3.377137e-05

SimMultiCorrData documentation built on May 2, 2019, 9:50 a.m.