Time series models based on generalized linear models: Some further results

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Abstract

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.
Original languageEnglish
Pages (from-to)506-511
JournalBiometrics
Volume50
Issue number2
DOIs
Publication statusPublished - Jun 1994

Citation

Li, W. K. (1994). Time series models based on generalized linear models: Some further results. Biometrics, 50(2), 506-511. doi: 10.2307/2533393

Keywords

  • Autoregressive moving average models
  • Generalized linear model
  • Longitudinal data
  • Quasi-likelihood
  • Score statistic

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