Discriminant function analysis , pattern recognition technique

The discriminant analysis techniques discussed above rely for their effective use on a priori knowledge of the underlying parent distribution function of the variates. In analytical chemistry, the assumption of multivariate normal distribution may not be valid. A wide variety of techniques for pattern recognition not requiring any assumption regarding the distribution of the data have been proposed and employed in analytical spectroscopy. These methods are referred to as non-parametric methods. Most of these schemes are based on attempts to estimate P(x g > and include histogram techniques, kernel estimates and expansion methods. One of the most common techniques is that of K-nearest neighbours. 

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