Bivariate Zero-Inflated Negative Binomial Model Estimation
This package is based on a draft paper ``A Bivariate Zero-Inflated Negative Binomial Model For Identifying Underlying Dependence" (Hunyong Cho, John Preisser, Chuwen Liu \& Di Wu 2019+ (In preparation)).
See the following toy example for fun.
library(bzinb) # generating n x 2 matrix (two vectors) set.seed(2) data1 <- rbzinb(n = 20, a0 = 1, a1 = 2, a2 = 1, b1 = 1, b2 = 1, p1 = 0.5, p2 = 0.2, p3 = 0.2, p4 = 0.1) # getting the underlying correlation (rho) through maximum likelihood estimate. bzinb(xvec = data1[,1], yvec = data1[,2], showFlag = F) # generating (additional two vectors) set.seed(3) data2 <- rbzinb(n = 20, a0 = 2, a1 = 1, a2 = 1, b1 = 1, b2 = 1, p1 = 0.5, p2 = 0.2, p3 = 0.2, p4 = 0.1) data3 <- t(cbind(data1, data2)) pairwise.bzinb(data3, showFlag = TRUE)
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