[R] obtaining the discriminant line from lda

[Clayton Springer]

Dear R folks,

Thanks to all your help before I have loaded a 1-D toy data set into
R and did LDA on it. The toy data has Class=0 if value>0.

> XY <-- read.table ("test.xy",header=T )
> XY              
     X.Class       value
1          0  60.4897262
2          0  32.9554489
3         -1 -53.6459189
4          0  44.4450579
.
.
.
998       -1 -43.4183157
999        0   7.9865092
1000      -1  -8.2279180
> XY.lda <- lda(X.Class ~ value,XY)
> XY.lda
Call:
lda.formula(X.Class ~ value, data = XY)

Prior probabilities of groups:
   -1     0 
0.521 0.479 

Group means:
       value
-1 -48.66322
0   49.91819

Coefficients of linear discriminants:
            LD1
value 0.0357248
> XY.lda$svd
[1] 55.63543
> XY.lda$class
NULL
> XY.lda$posterior
NULL

Question #1: How do I obtain the line that lda thinks divides the
two groups?  (which here it is between 1 and 2.)

Next I load in a test set for prediction:

> Predict0
   value
1    -10
2     -9
3     -8
4     -7
5     -6
6     -5
7     -4
8     -3
9     -2
10    -1
11     0
12     1
13     2
14     3
15     4
16     5
17     6
18     7
19     8
20     9
21    10

> Predict0.lda <- predict(XY.lda,Predict0)
> Predict0.lda$class
 [1] -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 0  0  0  0  0  0  0  0  0 

For those who don't want to count this shows that the dividing
line is somewhere between 1 & 2, even though my toy data set
can be perfectly divided at 0.  I had not expected (Fischer's) LDA
to behave this way.

Question #2:  Are there parameter adjustments and/or other LDA methods
where I can get the expected dividing surface at 0. (presumability
a classification tree would choose the line I desire, but I want
a lda method that does this.) 

If I am not being clear let me know, 

Thanks in advance,

Clayton
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