Negative binomial (NB-C): generic synthetic canonical negative binomial data and model
Description
nbc_syn is a generic function for developing synthetic NB-C data and a model given
user defined specifications.
Usage
nbc_syn(nobs=50000, alpha=1.15, xv = c(-1.5, -1.25, -.1))
Arguments
nobs
number of observations in model, Default is 50000
alpha
NB-C heterogeneity or ancillary parameter
xv
predictor coefficient values. First argument is intercept. Use as
xv = c(intercept , x1_coef, x2_coef, ...)
Details
Create a synthetic canonial negative binomial (NB-C) regression model using the
appropriate arguments. Model data with predictors indicated as a group with
a period (.). Data can be modeled using the ml.nbc.r function in the COUNT
package. See examples.
Value
nbcy
Canonical negative binomial (NB-C) response; number of counts
sim.data
synthetic data set
Author(s)
Joseph M. Hilbe, Arizona State University, and
Jet Propulsion Laboratory, California Institute of Technology
Andrew Robinson, Universty of Melbourne, Australia.
References
Hilbe, J.M. (2011), Negative Binomial Regression, second edition, Cambridge University Press.