intercorr_cont_nb: 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 calculates a k_cont x k_nb intermediate matrix of correlations for the k_cont continuous and k_nb Negative Binomial variables. It extends the method of Amatya & Demirtas (2015, doi: 10.1080/00949655.2014.953534) to continuous variables generated using Headrick's fifth-order polynomial transformation and regular or zero-inflated NB variables. Here, the intermediate correlation between Z1 and Z2 (where Z1 is the standard normal variable transformed using Headrick's fifth-order or Fleishman's third-order method to produce a continuous variable Y1, and Z2 is the standard normal variable used to generate a Negative Binomial variable via the inverse CDF method) is calculated by dividing the target correlation by a correction factor. The correction factor is the product of the upper Frechet-Hoeffding bound on the correlation between a Negative Binomial variable and the normal variable used to generate it and the power method correlation (described in Headrick & Kowalchuk, 2007, doi: 10.1080/10629360600605065) between Y1 and Z1. The function is used in intercorr and corrvar. This function would not ordinarily be called by the user.

Usage

intercorr_cont_nb(method = c("Fleishman", "Polynomial"), constants = NULL,
  rho_cont_nb = NULL, size = NULL, mu = NULL, p_zinb = 0,
  nrand = 100000, seed = 1234)

Arguments

method	the method used to generate the k_cont continuous variables. "Fleishman" uses a third-order polynomial transformation and "Polynomial" uses Headrick's fifth-order transformation.
constants	a matrix with k_cont rows, each 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_nb	a k_cont x k_nb matrix of target correlations among continuous and Negative Binomial variables; the NB variables should be ordered 1st regular, 2nd zero-inflated
size	a vector of size parameters for the Negative Binomial variables (see stats::dnbinom); the order should be 1st regular NB variables, 2nd zero-inflated NB variables
mu	a vector of mean parameters for the NB variables (*Note: either prob or mu should be supplied for all Negative Binomial variables, not a mixture; default = NULL); order the same as in size; for zero-inflated NB this refers to the mean of the NB distribution (see VGAM::dzinegbin)
p_zinb	a vector of probabilities of structural zeros (not including zeros from the NB distribution) for the zero-inflated NB variables (see VGAM::dzinegbin); if p_zinb = 0, Y_{nb} has a regular NB distribution; if p_zinb is in (-prob^size/(1 - prob^size), 0), Y_{nb} has a zero-deflated NB distribution and p_zinb is not a probability; if p_zinb = -prob^size/(1 - prob^size), Y_{nb} has a positive-NB distribution (see VGAM::dposnegbin); if length(p_zinb) < length(size), the missing values are set to 0 (and ordered 1st)
nrand	the number of random numbers to generate in calculating the bound (default = 10000)
seed	the seed used in random number generation (default = 1234)

Value

a k_cont x k_nb matrix whose rows represent the k_cont continuous variables and columns represent the k_nb Negative Binomial variables

References

Please see references for intercorr_cont_pois.

See Also

find_constants, intercorr, corrvar

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