Have anyone had problems with the tolerance in discriminant analysis if the input variables for such anlaysis have previously been transformed by Burnaby's method?
We are studing the population structure of a fish species in the North Atlantic. 17 variables (distances between landmarks) have been measured for each fish , following the truss network model and in adition we have measured some other structures as eye diameter, fin lengths, etc. We have 4391 cases, distributed in seven geographical locations. In order to eliminate the size influence, we have used two methods, i.e., residuals against standart length, and the Burnaby's method. Once we have removed the size effect, we run a discriminant analysis to observe differences between areas. We have no problem if we use the residuals as input for the discriminant analysis. But we cannot perform a discriminant analysis using as input the Burnaby's transformed variables, because we have problems with the tolerance of the variables: the matrix is ill-conditioning. The problem doesn't seem to be in a particular variable or in a group of data (data has been carefully screened for outliers). Simply, there is some redundancy. However the correlations between variables are not particularly high. We have also study if the problem is in the data, running the Discriminant Analysis with different combinations of the seven locations we have. But the results don't give us a clue. For example, when doing the analyses with four locations (a-d), it works. But as soon, as you introuduce some of the other three (e-g), it fails. However, some combinations of e, f or g, with other locations it works. Thus, not neccessarily the problem is in the locations e-g, but when these locations are together with some other, but there is no clear pattern. The same thing occurs with the variables. We have removed the variable than enter at last step (when tolerance drops below the limit), but then is another variable which cause problems, and if removed is another one and so on. We suspect that the problem is relared with the way that burbany method estimate the transformed variables. Can anyone help us? Thanks in advance, Lola <>< <>< <>< <>< <>< <>< <>< <><=20 Dolores Garabana Barro Institute of Fisheries Research Eduardo Cabello, 6 36208 Vigo (Spain) e-mail: [EMAIL PROTECTED] ><> ><> ><> <>< ><> ><> ><> ><> == Replies will be sent to list. For more information see http://life.bio.sunysb.edu/morph/morphmet.html.
