Bivariate Zero-Inflated Negative Binomial Model Estimator

Provides a maximum likelihood estimation of Bivariate Zero-Inflated Negative Binomial (BZINB) model or the nested model parameters. Also estimates the underlying correlation of the a pair of count data. See Cho, H., Preisser, J., Liu, C., and Wu, D. (In preparation) for details.


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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Reference manual

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install.packages("bzinb")

1.0.1 by Hunyong Cho, a month ago


Browse source code at https://github.com/cran/bzinb


Authors: Hunyong Cho , Chuwen Liu , Jinyoung Park , Di Wu


Documentation:   PDF Manual  


GPL-2 license


Imports Rcpp

Linking to Rcpp, BH


See at CRAN