A time series of Poisson counts; Polio data
A serially correlated time series of Poisson counts using a GLMM framework
Model descriptionAs 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.
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)