Fleishman.coef.NN: Computes the Fleishman coefficients for each continuous...

In BinOrdNonNor: Concurrent Generation of Binary, Ordinal and Continuous Data

Description

The function checks whether the skewness and kurtosis parameters violates the universal equality given in Demirtas, Hedeker, Mermelstein (2012) and computes the Fleishman coefficients for each continuous variable with pre-specified skewness and kurtosis values by solving the Fleishman's polynomial equations using BBsolve function in BB package.

Usage

Fleishman.coef.NN(skew.vec, kurto.vec)

Arguments

skew.vec	The skewness vector for continuous variables.
kurto.vec	The kurtosis vector for continuous variables.

Value

An matrix with four columns corresponding to the four Fleishman coefficients, and number of rows corresponding to number of continuous variables. The i-th row contains the estimates of the four Fleishman coefficients a, b, c and d for the i-th continuous variable with i-th pre-specified skewness and kurtosis values.

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.

Fleishman, A.I. (1978). A method for simulating non-normal distributions. Psychometrika, 43(4), 521-532.

Examples

# Consider four continuous variables, which come from
# Exp(1),Beta(4,4),Beta(4,2) and Gamma(10,10), respectively.
# Skewness and kurtosis values of these variables are as follows:

skew.vec <- c(2,0,-0.4677,0.6325)
kurto.vec <- c(6,-0.5455,-0.3750,0.6)
coef.est <- Fleishman.coef.NN(skew.vec, kurto.vec)

Example output

Loading required package: GenOrd
Loading required package: mvtnorm
Loading required package: Matrix
Loading required package: MASS
Loading required package: OrdNor
Loading required package: corpcor
  Successful convergence.
  Successful convergence.
  Successful convergence.
  Successful convergence.

BinOrdNonNor documentation built on March 22, 2021, 9:07 a.m.