bzinb.se: The bivariate zero-inflated negative binomial distribution -...
In Hunyong/BZINB: Bivariate Zero-Inflated Negative Binomial Model Estimator

Description Usage Arguments Value Author(s) References Examples

Standard errors of the BZINB distribution parameter estimates are calculated based on maximum likelihood estimation. If param is NULL, the parameters are first estimated by bzinb function.

1	bzinb.se(xvec, yvec, a0, a1, a2, b1, b2, p1, p2, p3, p4, param = NULL, ...)

`xvec, yvec`	a pair of bzinb random vectors. nonnegative integer vectors. If not integers, they will be rounded to the nearest integers.
`a0, a1, a2`	shape parameters of the latent gamma variables. They must be positive.
`b1, b2`	scale parameters for the latent gamma variables. They must be positive.
`p1, p2, p3, p4`	proportions summing up to 1 (`p1 + p2 + p3 + p4 = 1`). `p1` is the probability of both latent Poisson variables being observed. `p2` is the probability of only the first Poisson variables being observed. `p3` is the probability of only the second Poisson variables being observed, and `p4` is the probability of both Poisson variables being dropped out.
`param`	a vector of parameters (`(a0, a1, a2, b1, b2, p1, p2, p3, p4)`). See `bzinb` for more detail.
`...`	Other arguments passed on to `bzinb` function, when `param` is `NULL`.

Standard error of rho, logit.rho, a0, a1, a2, b1, b2, p1, p2, p3, and p4 estimates, variance-covariance matrix (vcov) and information matrix. See bzinb for more detail. iter is NA, if the param is given.

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

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

set.seed(1)
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)
bzinb.se(xvec = data1[,1], yvec = data1[,2], 
         param = c(5.5, 0.017, 0.017, 0.33, 0.36, 
                   0.53, 0.30, 0.08, 0.09))