Manuel--
I apologize in advance for not answering the exact question you ask about
packages. [It is included in some geostatistics packages in terms of
semivariance, nugget, sill, etc.]
In ecological data, time to independence is very scale dependent. There's
autocorrelation at scales of
Many ecological journals either encourage or require that the dataset behind a
paper be submitted to a repository such as dryad, or included as an electronic
appendix. Even if your university does not have institutional subscription to
all journals, some journals like Ecosphere are
Or, if the component matrices need to be numeric with species names as row
names and sites as column names, Dave Roberts' labdsv package has matrify()
that does that and fills in the unseen combinations with 0s as opposed to
NAs. Converting {site, taxon, abundance} triplets to matrix form is a
Eric--
If you don't care about "leaf-like" shape, you have 6 X,Y points defined
plus a pair of points at the maximum width at some undefined distance from
the apex. Assuming bilateral symmetry, and assuming that the maximum width
is at 50% from apex to base, you have 5 points {0,0,
Bruce--
You don't specify if you want the intersected polygons: 1 record for each
polygon intersection of species rangemap and habitat polygon, or just a
list of which habitat type polygons are at least partially within the
species' rangemap polygons.
The former is much slower but can give you
Pierre--
That's actually an easy question. Look at the vegan package
https://cran.r-project.org/web/packages/vegan/index.html. It has functions
for various dissimilarity & distance metrics (and can use distance matrices
from other packages such as ecodist), MDS and allied processes, anosim and
Andre--
I'm not completely clear on what you are trying to do. My best guess
interpretation of "my raster sometimes goes from one
to several contiguous cells in all directions" is that you have a raster
that you are aggregating into blobs of contiguous cells based on values in
one layer. You
Manuel--
The proper package depends entirely on what your data are: how many sites
you collect counts for, whether those sites are a probability sample over
an area or the only locations you are making inferences about (e.g., census
counts), whether those counts have Poisson error, overdispersion
Conny--
Note that Jari's surface fitting is using ordination scores on the
right-hand predictor size of the formula, with some z as the response.
If you need something about species composition as your _response_ variable
in a linear model (e.g., with time, disturbance type, and treatment as
Katia--
Your attached script didn't come through. as attachments are stripped by
the mailing list.
However, I can give you 2 generic answers.
First, if your vector of species names is called SpList, and your data are
in a big SpatialPointsDataFrame spdf
for (SP in SpList) {
spSP <-
in the
package survival.
Warm regards,
Mehdi
On Fri, Jul 24, 2015 at 4:11 AM, Philippi, Tom tom_phili...@nps.gov
wrote:
Mehdi--
Based on the example datasets germination and chickweed, drc would work
with you using the final count of emergence as the number of seeds at risk
of germinating. If you
Mehdi--
Based on the example datasets germination and chickweed, drc would work
with you using the final count of emergence as the number of seeds at risk
of germinating. If you get a satisfactory fit from one of the 6 or so
function forms it supports for dose-response, you may be fine. [I have
Luis--
I assume that especie is a factor, else it would be multiple regression.
You do not give much information on what you want your graph to look like.
If you want the linear regression line for each especie, with confidence
bands around those lines, you can use ggplot2 (untested code):
Amanda--
I'm not sure I would be convinced by you analyses, as I don't think your
statistical model corresponds to your sampling or data generating process.
But, I'd need to know more information about the response design (data
collection) to make any suggestions.
For binomial or quasi-, you
Matthew--
Do you get what you want in terms of estimated effect of ecosystem type by
dropping Elevation from your model? That difference would include the
component of the response to the difference in mean elevation.
If not, from a pure parameter estimation perspective, if your simulated
data
Tim--
When I had decreasing MDL over a monitoring period, I looked at the
distribution of the values collected under the later, lower MDL (MDL2) that
were MDL1 (including BDL2), then used that distribution (estimated via
kerneling) to simulate/impute values under the earlier MDL1. In my
In order to glue tide height (or tide current) onto each fish position
observation:
1: Convert dates times to POSIXct (do it all in GMT to avoid DST issues!).
2: Consider using NOAA tide data, available as 6 minute interval time
series http://tidesandcurrents.noaa.gov/api/ . Luke Miller has
Maria--
I believe that your problem is with the line:
s1-readShapePoly(shapes[i], verbose=T)
It may be as simple as removing the quote marks:
s1-readShapePoly(shapes[i], verbose=T)
as shapes is a vector of character. However, I use rgdal::readOGR() to
read shapefiles, so your mileage may vary,
Maria--
I believe that your NAs from the extract are because those polygons do not
cover at least 1 center point of a pixel in your bioclim rasters. One
solution is to use small=TRUE in your call to extract: see ?extract for
more information. Another would be to pull the bioclim data with
I would start with SDMTools
On Wed, Apr 17, 2013 at 10:22 AM, Bruce Miller batsnc...@gmail.com wrote:
Hi all,
Any/*R*/ packages that include the equivalent of FRAGSTATS for
fragmentation indices?
Tnx
Bruce
[[alternative HTML version deleted]]
Jay--
I'm not sure how one would combine SEM / graphical models with
compositional dissimilarity as a response. You might be able to fit a
series of models in adonis() or capscale(), comparing just direct factors
to direct + intermediate, etc.. I don't have any good ideas on how you
might test
At least some errata at:
http://www.maths.bath.ac.uk/~jjf23/ELM/
http://www.maths.bath.ac.uk/~jjf23/ELM/errata.html
Tom 2
On Fri, Nov 30, 2012 at 10:47 AM, Dave Roberts
dvr...@ecology.msu.montana.edu wrote:
Philip,
IS there an online errata,or do you just have to be smart and diligent?
I would also recommend considering Faraway (2006) Extending the linear
model with R
and the draft chapters of Doug bates' lme4 book:
http://lme4.r-forge.r-project.org/book/
The choice between Pinheiro Bates, Zuur, and Faraway is part style and
part specific applications of mixed models: I need
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