On Wed, 2010-06-02 at 13:45 +0200, Joris Meys wrote:
Hi Diederik,
I can't say immediately why your models fail without seeing the data and
running a number of tests. You could play around with the other parameters,
as the problem might be related to the optimization algorithm.
A different
On Thu, Jun 3, 2010 at 9:27 AM, Gavin Simpson gavin.simp...@ucl.ac.ukwrote:
vegan is probably not too useful here as the response is univariate;
counts of ducks.
If we assume that only one species is counted and of interest for the whole
research. I (probably wrongly) assumed that data for
On Thu, 2010-06-03 at 17:00 +0200, Joris Meys wrote:
On Thu, Jun 3, 2010 at 9:27 AM, Gavin Simpson gavin.simp...@ucl.ac.ukwrote:
vegan is probably not too useful here as the response is univariate;
counts of ducks.
If we assume that only one species is counted and of interest for the
See below.
On Thu, Jun 3, 2010 at 5:35 PM, Gavin Simpson gavin.simp...@ucl.ac.ukwrote:
On Thu, 2010-06-03 at 17:00 +0200, Joris Meys wrote:
On Thu, Jun 3, 2010 at 9:27 AM, Gavin Simpson gavin.simp...@ucl.ac.uk
wrote:
vegan is probably not too useful here as the response is
Correction : That should give some clarity on the question whether it is the
optimization of GAMLSS that goes wrong, or whether the problem is inherent
to the data.
On Thu, Jun 3, 2010 at 7:00 PM, Joris Meys jorism...@gmail.com wrote:
See below.
On Thu, Jun 3, 2010 at 5:35 PM, Gavin Simpson
Dear all,
I am using gamlss (Package gamlss version 4.0-0, R version 2.10.1, Windows XP
Service Pack 3 on a HP EliteBook) to relate bird counts to habit variables.
However, most models fail because “the global deviance is increasing” and I am
not sure what causes this behaviour. The dataset
Hi Diederik,
I can't say immediately why your models fail without seeing the data and
running a number of tests. You could play around with the other parameters,
as the problem might be related to the optimization algorithm.
A different approach would be using the methods in the vegan package.
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