Template-Type: ReDIF-Paper 1.0
Title: Generalized linear autoregressions
Author-Name: Neil Shephard
Creation-Date: 199502
Abstract: This paper develops a class of autoregressive and moving average
  	models which extend the generalized linear model. Likelihood and
  	quasi-likelihood estimation procedures are developed which allow the
  	models to be easily estimated and tested. Several examples are given
  	which illustrate the usefulness and simplicity of the approach
  	advocated in this paper.
Keywords: ARCH, autoregression, binomial, categorical data, count data,
  	diagnostic checking, exponential family, gamma, generalized linear
  	models, martingale difference, moving average, overdispersion,
  	poisson.
Series: W
Number: 8.
File-URL: http://www.nuff.ox.ac.uk/economics_wp/w8/glar.zip
File-Format: Application/postscript/zipped
File-Size: 74,675 bytes
Handle: RePEc:nuf:econwp:0008