calc.bin.prob.NB

This function implements Step 1 of the algorithm. It collapses each discrete
outcome from the negative binomial distribution into a binary
probability and determines a dichotomous threshold for each variable.

Generate multivariate discrete data with generalized Poisson, negative binomial and binomial marginal distributions using user-specified distribution parameters and a target correlation matrix. The method is described in Cheng and Demirtas (2026) <doi:10.48550/arXiv.2602.07707>.

Chak Kwong (Tommy) Cheng

MultiDiscreteRNG

Generate Multivariate Discrete Data

Hakan Demirtas

calc.bin.prob.NB function

<dl><dt>NB.r.vec</dt>
<dd>vector of number of trials</dd>
<dt>NB.prob.vec</dt>
<dd>vector of probabilities</dd></dl>

Arguments

Collapse discrete negative binomial outcomes to binary variables — calc.bin.prob.NB

<dl>

<dt>NB.r.vec</dt>
<dd>vector of number of trials</dd>


<dt>NB.prob.vec</dt>
<dd>vector of probabilities</dd>

</dl>

calc.bin.prob.NB: Collapse discrete negative binomial outcomes to binary variables

Description

Usage

Value

Arguments

Examples