# weighted.pc: Weighted Pearson Correlation (WPC) based on bivariate... In bzinb: Bivariate Zero-Inflated Negative Binomial Model Estimator

## Description

weighted.pc calculates Pearson's correlation with less weights for pairs containing zero(s). The weights are determined by BZINB model.

## Usage

 `1` ```weighted.pc(xvec, yvec, param = NULL, ...) ```

## Arguments

 `xvec, yvec` a pair of bzinb random vectors. nonnegative integer vectors. If not integers, they will be rounded to the nearest integers. `param` a vector of parameters (`(a0, a1, a2, b1, b2, p1, p2, p3, p4)`). See `bzinb` for details. If `param` is `null`, it will be estimated by `bzinb()`. `...` optional arguments used passed to `bzinb`, when `param` is `null`.

## Value

weighted Pearson correlation (WPC) estimate

## Author(s)

Hunyong Cho, Chuwen Liu, Jinyoung Park, and Di Wu

## References

Cho, H., Preisser, J., Liu, C., and Wu, D. (In preparation), "A bivariate zero-inflated negative binomial model for identifying underlying dependence"

## Examples

 ```1 2 3 4 5 6 7 8 9``` ```# generating a pair of random vectors set.seed(2) data1 <- rbzinb(n = 20, a0 = 1, a1 = 1, a2 = 1, b1 = 1, b2 = 1, p1 = 0.5, p2 = 0.2, p3 = 0.2, p4 = 0.1) weighted.pc(xvec = data1[,1], yvec = data1[,2], param = c(0.769, 0.041, 0.075, 3.225, 1.902, 0.5, 0.084, 1e-20, 0.416)) weighted.pc(xvec = data1[,1], yvec = data1[,2]) ```

bzinb documentation built on Dec. 8, 2019, 9:12 a.m.