bzip.a | R Documentation |
random generation (rbzip.a
), maximum likelihood estimation (bzip.a
),
and log-likelihood. (lik.bzip.a
) for the bivariate zero-inflated Poisson (A)
distribution with parameters equal to (m0, m1, m2, p)
.
lik.bzip.a(xvec, yvec, m0, m1, m2, p, param = NULL)
rbzip.a(n, m0, m1, m2, p, param = NULL)
bzip.a(xvec, yvec, tol = 1e-06, initial = NULL, showFlag = FALSE)
xvec , yvec |
a pair of BZIP (A) random vectors. nonnegative integer vectors. If not integers, they will be rounded to the nearest integers. |
m0 , m1 , m2 |
mean parameters of the Poisson variables. must be positive. |
p |
zero-inflation probability |
param |
a vector of parameters ( |
n |
number of observations. |
tol |
tolerance for judging convergence. |
initial |
starting value of param for EM algorithm, a vector of nine values. |
showFlag |
if |
rbzip.a
gives a pair of random vectors following BZIP (A) distribution.
bzip.a
gives the maximum likelihood estimates of a BZIP (A) pair.
lik.bzip.a
gives the log-likelihood of a set of parameters for a BZIP (A) pair.
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"
Li, C. S., Lu, J. C., Park, J., Kim, K., Brinkley, P. A., & Peterson, J. P. (1999). Multivariate zero-inflated Poisson models and their applications. Technometrics, 41, 29-38.
# generating a pair of random vectors
set.seed(1)
data1 <- rbzip.a(n = 20, m0 = 1, m1 = 1, m2 = 1, p = 0.5)
lik.bzip.a(xvec = data1[, 1], yvec = data1[ ,2],
m0 = 1, m1 = 1, m2 = 1, p = 0.5)
bzip.a(xvec = data1[,1], yvec = data1[,2], showFlag = FALSE)
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