Negative binomial (NB1): generic synthetic linear negative binomial data and model

Description

nb1_syn is a generic function for developing synthetic NB1 data and a model given user defined specifications.

Usage

nb1_syn(nobs=50000, delta=1, xv = c(1, 0.75, -1.25))

Arguments

Details

Create a synthetic linear negative binomial (NB1) regression model using the appropriate arguments. Model data with predictors indicated as a group with a period (.). See examples.

Data can be modeled using the ml.nb1.r function in the COUNT package, or by using the gamlss function in the gamlss package, using the "family=NBII" option.

Value

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, nbc_syn

Examples

sim.data <- nb1_syn(nobs = 5000, delta = .5, xv = c(.5, 1.25, -1.5))
mynb1 <- ml.nb1(nb1y ~ . , data = sim.data)
mynb1

## Not run: 
# use gamlss to model NB1 data
library(gamlss)         
sim.data <- nb1_syn(nobs = 5000, delta = .5, xv = c(.5, 1.25, -1.5))
mynb1 <- gamlss( nb1y ~ . , family=NBII, data = sim.data)
mynb1

## End(Not run)

## Not run: 
# default
sim.data <- nb1_syn()
dnb1 <- ml.nb1(nb1y ~ . , data = sim.data)
dnb1

## End(Not run)

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(COUNT)
Loading required package: msme
Loading required package: MASS
Loading required package: lattice
Loading required package: sandwich
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/COUNT/nb1_syn.Rd_%03d_medium.png", width=480, height=480)
> ### Name: nb1_syn
> ### Title: Negative binomial (NB1): generic synthetic linear negative
> ###   binomial data and model
> ### Aliases: nb1_syn
> ### Keywords: models negative binomial
> 
> ### ** Examples
> 
> 
> sim.data <- nb1_syn(nobs = 5000, delta = .5, xv = c(.5, 1.25, -1.5))
> mynb1 <- ml.nb1(nb1y ~ . , data = sim.data)
> mynb1
              Estimate          SE          Z        LCL        UCL
(Intercept)  0.4956615 0.011438133   43.33413  0.4732428  0.5180803
x1           1.2567946 0.005270121  238.47547  1.2464652  1.2671241
x2          -1.4983175 0.005125695 -292.31501 -1.5083639 -1.4882712
alpha        0.4587779 0.034287596   13.38029  0.3915742  0.5259816
> 
> ## Not run: 
> ##D # use gamlss to model NB1 data
> ##D library(gamlss)         
> ##D sim.data <- nb1_syn(nobs = 5000, delta = .5, xv = c(.5, 1.25, -1.5))
> ##D mynb1 <- gamlss( nb1y ~ . , family=NBII, data = sim.data)
> ##D mynb1
> ## End(Not run)
> 
> ## Not run: 
> ##D # default
> ##D sim.data <- nb1_syn()
> ##D dnb1 <- ml.nb1(nb1y ~ . , data = sim.data)
> ##D dnb1
> ## End(Not run)
> 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>