poisson_syn {COUNT}

Poisson : generic synthetic Poisson data and model

Description

poisson_syn is a generic function for developing synthetic Poisson data and a model given user defined specifications.

Usage

poisson_syn(nobs = 50000, off = 0, xv = c(1, -.5,  1))

Arguments

nobs

number of observations in model, Default is 50000

off

optional: log of offset variable

xv

predictor coefficient values. First argument is intercept. Use as xv = c(intercept , x1_coef, x2_coef, ...)

Details

Create a synthetic Poisson regression model using the appropriate arguments. Offset optional. Model data with predictors indicated as a group with a period (.). See examples.

Value

py

Poisson 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.

See Also

nb2_syn

Examples

# standard Poisson model with two predictors and intercept
sim.data <- poisson_syn(nobs = 500, xv = c(2, .75, -1.25))
mypo <- glm(py ~ . , family=poisson, data = sim.data)
summary(mypo)
confint(mypo)

# Poisson with offset and three predictors
oset <- rep(1:5, each=100, times=1)*100 
loff <- log(oset)   
sim.data <- poisson_syn(nobs = 500, off = loff, xv = c(1.2, -.75, .25, -1.3))
mypof <- glm(py ~ . + loff, family=poisson, data = sim.data)
summary(mypof)
confint(mypof)

# Poisson without offset, exponentiated coefficients, CI's
sim.data <- poisson_syn(nobs = 500, xv = c(2, .75, -1.25))
mypo <- glm(py ~ . , family=poisson, data = sim.data)
exp(coef(mypo))
exp(confint(mypo))

## Not run: 
# default (without offset)
sim.data <- poisson_syn()
dmypo <- glm( py ~ . , family=poisson, data = sim.data)
summary(dmypo)

## End(Not run)