Description Usage Arguments Value References See Also

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 *ρ_{Y1, Y2}* are simulated. Then the intermediate correlation is found as follows:

*ρ_{Z1, Z2} = \frac{1}{b} * log(\frac{ρ_{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 `Sigma_(Z1, Z2)`

> 1, `Sigma_(Z1, Z2)`

is set to 1; if `Sigma_(Z1, Z2)`

< -1,
`Sigma_(Z1, Z2)`

is set to -1

3) simulating regular and zero-inflated Negative Binomial variables.

The function is used in `intercorr`

and `corrvar`

and would not ordinarily be called by the user.

1 2 | ```
intercorr_nb(rho_nb = NULL, size = NULL, mu = NULL, p_zinb = 0,
nrand = 100000, seed = 1234)
``` |

`rho_nb` |
a |

`size` |
a vector of size parameters for the Negative Binomial variables (see |

`mu` |
a vector of mean parameters for the NB variables (*Note: either |

`p_zinb` |
a vector of probabilities of structural zeros (not including zeros from the NB distribution) for the zero-inflated NB variables
(see |

`nrand` |
the number of random numbers to generate in calculating the bound (default = 10000) |

`seed` |
the seed used in random number generation (default = 1234) |

the `k_nb x k_nb`

intermediate correlation matrix for the Negative Binomial variables

Please see references for `intercorr_pois`

.

`intercorr_pois`

, `intercorr_pois_nb`

,
`intercorr`

, `corrvar`

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