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.
KeywordsGeneralize Linear Model Hide Markov Model Markov Chain Model Caesarian Section Categorical Time Series
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