. The workhorse in QGIS is gdal as in rgdal, so suppose
something may be possible.
Best,
Patrick
Patrick,
I don't know the answer to your question but if you post it on the
R-sig-Geo list (https://stat.ethz.ch/mailman/listinfo/r-sig-geo) you
might get a satisfying answer faster.
Cheers,
Ivailo
if these are not
further classified into meaningful clusters; although you didn't
provide more details on how the forest patches relate to the regions
you wrote about) to run the analysis.
HTH,
Ivailo
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Dorothy Parker
On Wed, Feb 26, 2014 at 2:43 PM, Rajendra Mohan panda
rmp.iit@gmail.com wrote:
...
I have temperature data with negative values which I am not able to include
for my CCA ordination. ...
Rajendra, I am curious -- why are you not able to include the negative
values in the CCA ordination?
--
that although I don't have the book, I found the
radiation measures presented in the following paper:
McCune, B. and D. Keon. 2002. Equations for potential annual direct
incident radiation and heat load. Journal of Vegetation Science
13:603–606.
Cheers,
Ivailo
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says that it cannot find the boot function, so try
install.packages(boot) and then library(boot) if you have it
installed.
Cheers,
Ivailo
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On Wed, Jun 26, 2013 at 12:42 PM, Scott Foster scott.fos...@csiro.au wrote:
Hi again Ivailo,
Yes, the `offset' and the covariate are the same thing. Including them both
simply alters the functional form of the linear predictor in your model.
No, they are not collinear in the typical sense
On Tue, Jun 25, 2013 at 2:02 PM, Scott Foster scott.fos...@csiro.au wrote:
Hi Ivailo,
Good question. Difficult to answer, which is probably why you haven't had
any responses yet (that the list has seen).
If you include an offset term with a log link function then you are assuming
,
and if it's coefficient is around 1 to be taken as an indicator that
it is better that variable to be included in the model as an offset?
Cheers,
Ivailo
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, Structural Equations and Causal Inference, Cambridge
University Press, Cambridge, UK, 2000.
I recently stumbled on a great book on path modelling using PLS (with
R) that is freely downloadable at http://is.gd/BxqIEL
Ivailo
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the dendrogram), but I am not
sure if this wouldn't be regarded as circular reasoning.
Cheers,
Ivailo
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glht() from the multcomp package if you have a lm() object.
Cheers,
Ivailo
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) appears in the resulting list,
then you have R built with --enable-R-shlib.
And, if need be, how do I enable that option?
If needed, you can enable this option during the build process by
passing the option, e.g. ./config --enable-R-shlib, just before make.
Hope this helps,
Ivailo
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On Fri, Jun 15, 2012 at 6:20 PM, Michel Rapinski mrapi...@uottawa.ca wrote:
Hi Ivailo,
Do I run this command in R? Or in terminal? Maybe I should have added that
I have a mac, I don't know if that makes a difference.
Sorry, Michel, I missed to mention that ldd needs to be run in the
terminal
of the proportion of
hon-herbivores in the sample(s)?
Hope this helps,
Ivailo
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On Thu, May 10, 2012 at 3:51 PM, Wagner Tassinari
wtassin...@yahoo.com.br wrote:
Hi, I'd like to know how extract the QIC (quasi-likelihood information
criterion) in GEE model (using gee or geeglm commands) in R.
Hi Walter!
I think this - http://is.gd/myQ6IZ - could help.
Cheers,
Ivailo
;-)
Cheers,
Ivailo
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package and the destPoint() function seems
to do exactly what I was
searching for.
Cheers,
Ivailo
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(by using some of the spatial
R-packages) the geographic coordinates of the sapling plots at each
location that have not been explicitly georeferenced?
Cheers,
Ivailo
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the predictor variable
pred.var - sampledata[,1]
# perform MANOVA
model - adonis(dep.var ~ pred.var, permutations = 999,method =
canberra, strata = NULL)
Hope this helps,
Ivailo
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the
figure somewhere and post the link instead.
Cheers,
Ivailo
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not sure if the adonis() function would be appropriate
for the analysis you're trying to perform.
Cheers,
Ivailo
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'
Cheers,
Ivailo
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correlation coefficient. Function stressplot displays the nonlinear
fit and gives this statistic.
HTH,
Ivailo
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to any process.
Perhaps you need to try running your model on a 64-bit machine.
Cheers,
Ivailo
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routine dgesv: system is exactly
singular
Dear Marc,
as the error message says, it appears that the covariance matrix is
singular and.cannot be inverted. You should check your covariates to
see if one of these is not a function of the other.
Cheers,
Ivailo
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to study (common) species
responses to the three killing solutions. I don't have an answer for
that, but perhaps someone on the list might provide further insight...
Cheers,
Ivailo
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