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.