# corr.nn4pbo

##### Finds the underlying bivariate normal correlation given the correlation for a count-binary or count-ordinal pair.

This function computes the underlying bivariate normal correlation given the correlation for a pair of count and binary variables or a pair of count and ordinal variables.

##### Usage

`corr.nn4pbo(lam, p, PO.cor)`

##### Arguments

- lam
Rate parameter for the count variable.

- p
A vector of probabilities for an ordinal variable. The i-th element of the pvec is the cumulative probability defining the marginal distribution of the ordinal variable. If the variable has k categories, the i-th element of p will contain k-1 probabilities. The k-th element is implicitly 1.

- PO.cor
Pre-specified correlation for a pair of count and binary, or count and ordinal, variables.

##### Value

A tetrachoric correlation coefficient.

##### References

Amatya, A. & Demirtas, H. (2015). Simultaneous generation of multivariate mixed data with Poisson and normal marginals. Journal of Statistical Computation and Simulation, 85(15), 3129-3139.

Yahav, I. & Shmueli, G. (2012). On generating multivariate Poisson data in management science applications. Applied Stochastic Models in Business and Industry, 28(1), 91-102.

##### Examples

```
# NOT RUN {
corr.nn4pbo(0.5, c(0.2, 0.5), 0.235)
# }
```

*Documentation reproduced from package PoisBinOrdNor, version 1.6.1, License: GPL-2 | GPL-3*