In order to determine the parameters required in statistics for fitting a model, multiple methods can be used. In each of the cases, fitting involves the estimating of a small number of parameters from the data. Apart from estimating parameters, two important stages are the identification of a suitable model and the verification of the model. These smoothing methods can be used in a variety of ways: to aid understanding and produce smoothed plots, to identify a suitable parametric model from the shape of the smoothed data, or to focus on the effects of interest in order to eliminate complex effects which are of no use.
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