intercorr_cont: Calculate Intermediate MVN Correlation for Continuous...

In SimCorrMix: Simulation of Correlated Data with Multiple Variable Types Including Continuous and Count Mixture Distributions

Description

This function finds the intermediate correlation for standard normal random variables which are used in Fleishman's third-order (doi: 10.1007/BF02293811) or Headrick's fifth-order (doi: 10.1016/S0167-9473(02)00072-5) polynomial transformation method (PMT) using nleqslv. It is used in intercorr and intercorr2 and would not ordinarily be called by the user. The correlations are found pairwise so that eigen-value or principal components decomposition should be done on the resulting Sigma matrix. The Comparison of Correlation Methods 1 and 2 vignette contains the equations which were derived by Headrick and Sawilowsky (doi: 10.1007/BF02294317) or Headrick (doi: 10.1016/S0167-9473(02)00072-5).

Usage

intercorr_cont(method = c("Fleishman", "Polynomial"), constants = NULL,
  rho_cont = NULL)

Arguments

method	the method used to generate the continuous variables. "Fleishman" uses Fleishman's third-order polynomial transformation and "Polynomial" uses Headrick's fifth-order transformation.
constants	a matrix with each row a vector of constants c0, c1, c2, c3 (if method = "Fleishman") or c0, c1, c2, c3, c4, c5 (if method = "Polynomial"), like that returned by find_constants
rho_cont	a matrix of target correlations among continuous variables, does not have to be symmetric

Value

the intermediate matrix of correlations with the same dimensions as rho_cont

References

Please see additional references for SimCorrMix.

Fialkowski AC (2018). SimMultiCorrData: Simulation of Correlated Data with Multiple Variable Types. R package version 0.2.2. https://CRAN.R-project.org/package=SimMultiCorrData.

Headrick TC (2002). Fast Fifth-order Polynomial Transforms for Generating Univariate and Multivariate Non-normal Distributions. Computational Statistics & Data Analysis, 40(4):685-711. doi: 10.1016/S0167-9473(02)00072-5. (ScienceDirect)

Headrick TC, Kowalchuk RK (2007). The Power Method Transformation: Its Probability Density Function, Distribution Function, and Its Further Use for Fitting Data. Journal of Statistical Computation and Simulation, 77:229-249. doi: 10.1080/10629360600605065.

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

intercorr, intercorr2, nleqslv

SimCorrMix documentation built on May 2, 2019, 1:24 p.m.