Functional Linear Discriminant Analysis for Irregularly Sampled Curves

  title={Functional Linear Discriminant Analysis for Irregularly Sampled Curves},
  author={A Ames},
We introduce a technique for extending the classical method of Linear Discriminant Analysis to data sets where the predictor variables are curves or functions. This procedure, which we call functional linear discriminant analysis (FLDA), is particularly useful when only fragments of the curves are observed. All the techniques associated with LDA can be extended for use with FLDA. In particular FLDA can be used to produce classifications on new (test) curves, give an estimate of the discriminant… CONTINUE READING
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