| findintercorr_nb {SimMultiCorrData} | R Documentation |
Calculate Intermediate MVN Correlation for Negative Binomial Variables: Correlation Method 1
Description
This function calculates a k_nb x k_nb intermediate matrix of correlations for the Negative Binomial variables by
extending the method of Yahav & Shmueli (2012, doi: 10.1002/asmb.901). The intermediate correlation between Z1 and Z2 (the
standard normal variables used to generate the Negative Binomial variables Y1 and Y2 via the inverse cdf method) is
calculated using a logarithmic transformation of the target correlation. First, the upper and lower Frechet-Hoeffding bounds
(mincor, maxcor) on \rho_{y1,y2} are simulated. Then the intermediate correlation is found as follows:
\rho_{z1,z2} = (1/b) * log((\rho_{y1,y2} - c)/a)
, where a = -(maxcor * mincor)/(maxcor + mincor),
b = log((maxcor + a)/a), and c = -a. The function adapts code from Amatya & Demirtas' (2016) package
PoisNor-package by:
1) allowing specifications for the number of random variates and the seed for reproducibility
2) providing the following checks: if \rho_{z1,z2} >= 1, \rho_{z1,z2} is set to 0.99; if \rho_{z1,z2} <= -1,
\rho_{z1,z2} is set to -0.99
3) simulating Negative Binomial variables.
The function is used in findintercorr and rcorrvar.
This function would not ordinarily be called by the user.
Usage
findintercorr_nb(rho_nb, size, prob, mu = NULL, nrand = 100000,
seed = 1234)
Arguments
rho_nb |
a |
size |
a vector of size parameters for the Negative Binomial variables (see |
prob |
a vector of success probability parameters |
mu |
a vector of mean parameters (*Note: either |
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
the k_nb x k_nb intermediate correlation matrix for the Negative Binomial variables
References
Please see references for findintercorr_pois.
See Also
PoisNor-package, findintercorr_pois,
findintercorr_pois_nb,
findintercorr, rcorrvar