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A time series of Poisson counts; Polio data

A serially correlated time series of Poisson counts using a GLMM framework

Model description

As an example of a discrete valued time series we use the 'polio data' considered by Kuk & Cheng (1999). It is assumed that yi has a Poisson (lambdai) distribution, where

log(lambdai) = Xib + ui.

 

Here, Xi is a covariate vector, b is a vector of regression parameters and ui

is a first order autoregressive process.

 

Details

polio.pdf

 

Files

See "Navigation" box to the left.

  • .tpl:  Model file
  • .dat: Data file
  • .pin: Starting values for the numerical optimizer
  • .par: Result file (what you get when you compile and run your model)