[R] lda from MASS function

[Rishabh Gupta]

Hi all,
    I am using the lda function from the MASS library to measure the discriminance of different variables with respect to different
grouping variables by using

    lda( RESULTVARS[, 1:750] , GROUPVAR , tol=0 )    where RESULTVARS contains some 750 different variables.

Occasionally there is a variable within RESULTVARS that has the same values for all values of GROUPVAR, ie no variance so I get the
error:

Error in svd(X, nu = 0) : NA/NaN/Inf in foreign function call (arg 1)

As I understand it, this is due to the a division of zero in one svd function that is used by lda. The nature of my results are such
that every now and than I will get a case where all the values for a RESULTVARS variable are constant. Is there a way of getting
past this problem. For example, by using the tol=0 parameter I can avoid problems when the variables are the same within a
particular group. As far as I am concerned, cases where the variables are constant across all groups is saying that that variable
has zero discriminance.
Example values of the grouping variable are:
> d$subject
    [1] E D C B A H G K F I J E D C B A H G K F I J E D C B A H G K F I J E D C B A G H K F I J E D C B A H G K F I J E D C B A H G
K F I J E D C B A H G K F I J
    Levels:  A B C D E F G H I J K

Example values of the results variables with no errors are:
> d[,104]
 [1] 2.312308 2.957263 2.979431 2.764650 2.877694 3.078302 3.112324 2.906696 3.045316 1.995411 2.488661 2.976581 2.917944 3.089677
2.850058 2.758467
[17] 2.898870 2.966295 3.123338 3.130935 2.729223 2.831621 2.222380 2.461088 2.539655 2.267584 2.599100 2.575934 2.858999 2.311193
2.515690 2.490992
[33] 2.230635 2.846939 3.091381 3.072407 3.097286 2.878738 3.097788 3.155828 3.250491 3.095101 2.956129 3.157974 3.093765 2.682200
3.072632 2.931168
[49] 2.469290 2.909947 2.682943 2.985903 2.738458 2.828025 2.860262 3.112574 2.890100 2.813462 2.694520 3.058201 2.761940 2.835700
2.829152 2.834158
[65] 3.029300 2.870694 3.024452 2.909192 2.926210 2.530717 2.875842 2.798146 2.576489 2.690214 2.865670 2.499521 2.900491

and finally, example of the results variables WITH ERRORS are:
d[,105]
 [1] 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3
3 3 3 3 3 3 3 3 3 3 3 3 3

Can anyone suggest a workaround for this problem. Your help would be greatly appreciated.

Many Thanks For Your Help

Rishabh

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