Classical statistical models for regression, time series and longitudinal data analysis are generally useful in situations where data are approximately Gaussian and can be explained by some linear structure. These models are easy to interpret and the methods are theoretically well understood and investigated. However, the underlying assumptions may be too stringent and applications of the methods may be misleading in situations where data are clearly non-normal, such as categorical or counted data. Statistical modelling aims at providing more flexible model-based tools for data analysis.


Generalize Linear Model State Space Model Categorical Time Series Polio Case Structural Time Series Model 
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Copyright information

© Springer Science+Business Media New York 1994

Authors and Affiliations

  • Ludwig Fahrmeir
    • 1
  • Gerhard Tutz
    • 2
  1. 1.Seminar für StatistikUniversität MünchenMünchenGermany
  2. 2.Institut für Quantitative MethodenTechnische Universität BerlinBerlinGermany

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