This paper considers the problem of extending the classical moving average models to time series with conditional distributions given by generalized linear models. These models have the advantage of easy construction and estimation. Statistical modelling techniques are also proposed. Some simulation results and an illustrative example are reported to illustrate the methodology. The models will have potential applications in longitudinal data analysis. Copyright © 1994 International Biometric Society.
|Publication status||Published - Jun 1994|
CitationLi, W. K. (1994). Time series models based on generalized linear models: Some further results. Biometrics, 50(2), 506-511. doi: 10.2307/2533393
- Autoregressive moving average models
- Generalized linear model
- Longitudinal data
- Score statistic