[R] logistic regression for a data set with perfect separation

[Christoph Lehmann]

Dear R experts

I have the follwoing data
          V1 V2
1 -5.8000000  0
2 -4.8000000  0
3 -2.8666667  0
4 -0.8666667  0
5 -0.7333333  0
6 -1.6666667  0
7 -0.1333333  1
8  1.2000000  1
9  1.3333333  1

and I want to know, whether V1 can predict V2: of course it can, since
there is a perfect separation between cases 1..6 and 7..9

How can I test, whether this conclusion (being able to assign an
observation i to class j, only knowing its value on Variable V1)  holds
also for the population, our data were drawn from? 

Means, which inference procedure is recommended? Logistic regression
doesn't work, since the ML algorithm does not converge

1: Algorithm did not converge in: (if (is.empty.model(mt)) glm.fit.null else glm
.fit)(x = X, y = Y,
2: fitted probabilities numerically 0 or 1 occurred in: (if (is.empty.model(mt))
 glm.fit.null else glm.fit)(x = X, y = Y,

Many thanks for your help

Christoph
-- 
Christoph Lehmann <christoph.lehmann at gmx.ch>