Hi,
I am working on shark satellite tracking data and Im trying to use the
function kernelbb from the *adehabitatHR package *to calculate home range.
Some functions from *adehabitatHR *accept the use of a boundary and I was
wondering if there is a way to use a boundary with kernelbb?
Kind Re
Bradley Carlson writes:
>
>
> I'd be curious to hear from others if whether there are inherent flaws in
> this approach. I'm not terribly experienced in this area but this was the
> solution I came upon when I dealt with this issue myself.
>
There's a bit more information, and a variety of
Kendra,
Something is wrong in X or P; find out what the foreign function call is
and then you may be able to track down the offending data problem.
Maybe a logarithm somewhere? This is probably not much help; I don't
have much experience with envfit.
Stephen
On 12/03/2013 07:06 PM, Mitchel
Alexandre,
I'll leave it to Sarah to advise you on MRM (and I agree with Jari that
the method you're describing is not going to work). I'll just add that it
is not clear to me why the predictors (even geographic distance) have to
be treated as distances to partition the variance in composition. I'
Hi,
Not only odd, but impossible. If you have a model y ~ x1, and you *add* a new
explanatory variable, you cannot get worse in raw R2. You can get worse in
adjusted R2. You can also get worse if you add variables to a matrix for which
you calculate distances. So dist(y) ~ dist([x1]) can have h
Hi,
That seems a bit odd: can you provide a reproducible example, off-list
if necessary?
Sarah
On Wed, Dec 4, 2013 at 12:50 PM, Alexandre Fadigas de Souza
wrote:
> Dear friends,
>
>My name is Alexandre and I am trying to analyze a dataset on floristic
> composition of tropical coastal ve
Dear friends,
My name is Alexandre and I am trying to analyze a dataset on floristic
composition of tropical coastal vegetation by means of variance partition,
according to the outlines of a Tuomisto's recent papers, specially
Tuomisto, H., Ruokolainen, L., Ruokolainen, K., 2012. Modelling n
Thank you, Peter!
Attila
2013/12/3 Peter Solymos
> Attila,
>
> See paper and R code by Millar et al. 2011 for a solution based on 'glm':
> http://www.esapubs.org/archive///ecol/E092/146/
>
> Peter
>
> --
> Péter Sólymos, Dept Biol Sci, Univ Alberta, T6G 2E9, Canada AB
> soly...@ualberta.ca, Ph