R help - Aug 2001 - converting BMDP 8V mixed model treatment to R ?

I am trying to translate a given BMDP 8V problem treatment to something
approximately equivalent in nlme package (or base R, if sufficient).
(Of course, it is not my goal to end there. I want to get access to the
advanced flexibility of a more modern treatment.) Here is the problem
statement in BMDP control language:

/input  title='Augenbewegungen'.
        variables=4.
        file='latm.dat'.
        format='11x,f7.0,f7.0,f12.4,f10.0'.
/variables namesllat,rlat,vg,diff.
/design
ndep = 4.
level=21,2,2,9,3.
names = pers,retest,direct,flicker,ground.
random = pers.
fixed = retest,ground,direct,flicker.
model = 'P,R,G,D,F'.
/end.
/finish.

I tried in R (some minor differences in variable naming):

latm <- read.table( "latm.dat" )
latm.aov <- aov( llat ~ direct * flicker *ground *retest +person
	+ Error( person : ( direct * flicker *ground *retest )))

Indeed, summary(latm.aov) gives the same F tests than BMDP8V for the 1st part
of the evaluation. But I don't get variance components from this.

So it looks as if I have to change to mle from nmle package. I did not succeed
to translate this model to mle yet.

Trial-and-error fails mostly, because
the problem thrashes my system (FreeBSD, K6-233, 64MB). This is particularly
astonishing, as BMDP8V does it's work without problems on an old 24MB uVAX
VMS
system in mere 20 seconds CPU time. To run the above R partial solution
I have to wait for about an hour on a freshly loaded R, after making the
swapspace 3times as large as I use in normal work. There must be something
wrong, but I have no idea, how to advance.
-- 
Dipl.-Math. Wilhelm Bernhard Kloke
Institut fuer Arbeitsphysiologie an der Universitaet Dortmund
Ardeystrasse 67, D-44139 Dortmund, Tel. 0231-1084-257
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