Dear all,
I am currently working on GPS relocations and more specifically on the
study of territoriality (lynx and wolverine).
I'd like to use the function gBuffer from the rgeos package to apply a
buffer area to a home-range. What I'd like to get is the exact number of
points included in the
Dear all,
I'd like to test the two-side significance of an observed value being
lower or higher in comparison to a null distribution, but I don't know
how to build this in R code. Can anybody help me with some code or any R
function?
Let's say 'null.dist' the null distribution, 'obs' the
On 07/23/2013 12:06 PM, Cayetano Gutiérrez Cánovas wrote:
Dear all,
I'd like to test the two-side significance of an observed value being
lower or higher in comparison to a null distribution, but I don't know
how to build this in R code. Can anybody help me with some code or any R
function?
Thanks Bob / Dylan:
Bob:
I am concerned with the possibility of increase the risk of false
positives because two tests are actually performing.
What do you think of multiplying p-value by 2 (the number of tests) to
control risk?
set.seed(10)
rnorm(999)-null.dist
obs-2.5
alpha-0.05
also consider
?p.adjust
cheers
rob
** The new Bird Atlas is coming: http://www.bto.org/shop/bird-atlas ***
Dr Rob Robinson, Principal Ecologist
British Trust for Ornithology, The Nunnery, Thetford, Norfolk, IP24 2PU
Ph: +44 (0)1842 750050 E: rob.robin...@bto.org
Fx: +44 (0)1842
Once you create your buffer using gBuffer, you can run gIntersects using your
GPS relocations and the buffer, i.e:
within - gIntersects(GPS relocations, buffer)
And then just do a table on the resulting matrix to see which are true, i.e.:
table(within)
This should give you exact number of
Hi all,
is it possible to create an object of class
SpatialPoint/SpatialPointDataFrame, with a given resolution, constrained to
a certain SpatialPolygon?
In QGis, for example, I can create a rectangular layer of points and then
clip it to the extent of a polygon. The ideal solution in R would be
Hello,
I am relatively new to R and I am working through the code that is provided in
the book Numerical Ecology with
R:http://xa.yimg.com/kq/groups/19243105/1919134110/name/Numerical.pdf (pg 79)
and I have run across an error message that I can't seem to figure out.
I am using the vegan,
Dear R experts,
I fitted my spatial data to a glm.nb model. I decided to detect and correct
for spatial autocorrelation using ME{spdep}. If the glm.nb model is not
significant should I still check for spatial autocorrelation, i.e can
removing spatial autocorrelation uncover significance?
Also,
Dear R-list,
I'm looking at association btw individuals. Below is an example of the dataset.
id = individual i
neighb1 = first individual associated with individual i
neighb2 = second individual associated with individual i
Etc
nb_assoc = total number of association at time t
date = date in
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