Dear Matej,
This is a well-known problem of the LSCV algorithm. As the help page of
kernelUD explains,
Note that the cross-validation criterion cannot be minimized in some
cases. According to Seaman and Powell (1998) _"This is a difficult
problem that has not been worked out by statistical theoreticians, so no
definitive response is available at this time"_ (see Seaman and Powell,
1998 for further details and tricky solutions).
See also http://www.faunalia.com/pipermail/animov/2006-May/000165.html
as well as the links therein for a complete discussion on non convergence.
Hope this helps,
Clément Calenge
On 05/06/2010 03:18 PM, Matěj Lövy wrote:
Dear colleagues,
I try to understand something about calculation of HR in r-project
using ADEHABITAT package. I have read about and tried ot analyse our
data with LSCV method for smoothing parameter. but I received this
message:
Warning message:
In kernelUD(xy, id, h = "LSCV") : The algorithm did not converge
within the specified range of hlim: try to increase it
when I tried this: mydata<- kernelUD(xy, id, h = "LSCV").
could zou help me how to fix and understand this problem?
All the best and many thanks in advance
with kind regards
Matej Lovy
--
Clément CALENGE
Cellule d'appui à l'analyse de données
Office national de la chasse et de la faune sauvage
Saint Benoist - 78610 Auffargis
tel. (33) 01.30.46.54.14
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