classify

dear all,

I have some doubt concerning the function "classify":

1) if I use the method 'linear', what does it mean that the covariance matrix is computed by a pooled estimate ?

2) if I use the method 'quadratic', what does it mean that the covariance matrix is computed by a estimate stratified by group?

3) if I do not use 'mahalanobis' method, how are the distances computed in 'linear' and 'quadratic' methods?

4) am I correct that these distances are computed between the fit obtained from the training and the data in sample?

many thanks, any code of support to eventual answers is more than welcome.

Michele

Answer 1

[Ilya]

"Pooled" and "stratified" are conventional terms in the statistics literature. A pooled estimate is computed using all observations from all groups (classes). A stratified estimate is computed for each group (class) separately.

Every method in CLASSIFY computes the Mahalanobis distance from the center of each class (determined from the training data) and the data in sample. 'mahalanobis' method assigns an observation to the class with the minimal distance. All other methods estimate the posterior probabilities and assign an observation to the class with the largest posterior.