similar to: Comparing multiple distributions

Dear Lists, At several stations distributed regularly in space[1], we sampled repeatedly (4 times) the abundance of organisms and measured environmental parameters. I now want to compare the spatial distribution of various species (and test wether they differ or not), or to compare the distribution of a particular organism with the distribution of some environmental variable.

Hi everyone, I want to plot a 3D interpolation of the concentration of aquatic organisms. My goal would be to have the result represented as clouds with a density proportional to the abundance of organisms, so that I could fly (well, swim actually ;) ) through the scene and see the patches here and there. Basically, I want to do something like this: http://www.youtube.com/watch?v=27mo_Y-aU-c but

Hello everyone, I am looking at the joint spatial distribution of 2 kinds of organisms (estimated on a grid of points) and want to test for significant association or dissociation. My first question is: do you know a nice technique to do that, considering that I have a limited number of points (36) but that they are repeated (4 times)? I did GLMs to test for correlations between the

I have a list of scientific names in a data set. I would like to split the names into genus, species and subspecies. Not all names include a subspecies. Could someone show me how to do this? My example code is: a <- matrix(c('genusA speciesA', 10, 'genusB speciesAA', 20, 'genusC speciesAAA subspeciesA', 15,

Hi, I went ahead and implemented something. However: - I cannot garantie it gives correct results since, unfortunately, the data used in Syrjala 1996 is not published along with the paper. To avoid mistakes, I started by coding things in a fast and simple way and then tried to optimize the code. At least all versions given the same results. - As expected, the test is still quite slow

Apologies for the empty email earlier! I have species abundance data sampled at a weekly frequency or sometimes monthly depending on the year. The goal is to identify the dates in an annual cycle in which the cumulative abundance of a species reaches some threshold. Here's an example of the data for 1 species over an annual period: "mc_pheno" is the object created from this data:

Hi everyone, Hi ggplot users in particular, ggplot makes it very easy to plot things given their names when you use it interactively (and therefore can provide the names of the columns). qplot(x,foo,data=A) where A has columns (x,y,foo,bar) for example but I would like to use this from inside a function to which the name of the column is given. I cannot find an elegant way to make this

The function wtd.var(x,w) in Hmisc calculates the weighted variance of x where w are the weights. It appears to me that wtd.var(x,w) = var(x) if all of the weights are equal, but this does not appear to be the case. Can someone point out to me where I am going wrong here? Thanks. Tom La Bone [[alternative HTML version deleted]]

Is there a function that will allow me to run all model iterations if I specify a full model? I am using information criteria to choose between possible candidate models. I have been writing out all possible model combinations by hand, and I am always worried that I am missing models or have made a mistake somewhere. It is also difficult to alter models if I want to change a term. For example,

Hello everyone, I am (happily) using ggplot2 for all my plotting now and I wondered is there is an easy way to specify xlim and ylim somewhere when using the ggplot syntax, as opposed to the qplot syntax. Eg. qplot(data=mtcars,y=wt, x=qsec,xlim=c(0,30)) <-> ggplot(mtcars, aes(y=wt, x=qsec)) + geom_point() + ??? Indeed the ggplot syntax is in general more flexible and powerful and

Hello everyone, A recent (in 2.5 I suspect) change in R is giving me trouble. I want to apply a function (tolower) to all the columns of a data.frame and get a data.frame in return. Currently, on a data.frame, both apply (for arrays) and lapply (for lists) work, but each returns its native class (resp. matrix and list): apply(mydat,2,tolower) # gives a matrix lapply(mydat,tolower) # gives

Hello everyone, I often create some local "libraries" of functions (.R files with only functions in them) that I latter call. In scripts that call a function from such library, I would like to be able to test whether the function is already known in the namespace and, only if it is not, source the library file. I.e. what `require` does for packages, I want to do with my local

I'm having the most curious error while using the sem package. For the model I'm working with, I keep getting the following error: Error in J[cbind(1:n, observed)] <- 1 : subscript out of bounds I''ve used debug=TRUE with sem, and there don't appear to be any problems with model - there are no latent variables in this model. The variables in the covariance matrix

Dear List, I am trying to get R's terminal output to a file and to the terminal at the same time, so that I can walk through some tests and keep a log concurrently. The function 'sink' with the option split=TRUE seems to do just that. It works fine for most output but for objects of class htest, the terminal output is incomplete (the lines are there but empty). Here is an

Hello, I am facing a problem with lapply which I ''''think''' may be a bug. This is the most basic function in which I can reproduce it: myfun <- function() { foo = data.frame(1:10,10:1) foos = list(foo) fooCollumn=2 cFoo = lapply(foos,subset,select=fooCollumn) return(cFoo) } I am building a list of dataframes, in each of which I want to keep only column

Hello everybody, This is probably a classic but I cannot find an answer to this on the mailing list (i.e. with a google search restricted to the mailing list archive). Setting: par(new=T) plot(x,y) works but plot(x,y,new=T) doesn't while it is said in plot's help that ... arguments are passed to par. What am I missing? JiHO --- http://jo.irisson.free.fr/

Dear List, I am having problems running stepAIC with a negative binomial regression model.  I am working with data on manta ray abundance, using 20 predictor variables.  Predictors include variables for location (site), time (year, cos and sin of calendar day, length of day, percent lunar illumination), oceanography (sea surface temp mean and std, sea surface height mean and std), weather (cos

Hello all, I discovered that the pdf device uses fonts to represent "points" symbols (as in plot(...,type="p",...) ). Namely it uses ZapfDingbats with symbol U+25cf. This can lead to problems when the font is not available, or available in another version (such as points being replaced by other symbols, or worst: slightly displaced). Furthermore, it also causes

Hello everyone, I have two data.frames that look like calib: place zoom scale left 0.65 8 left 0.80 5.6 left 1.20 3 right 0.65 8.4 right 0.80 6 right 1.20 2.9 X: ... place zoom .... ... left 0.80 .... ... left 1.20 .... ... right 0.65 .... ... NA NA .... ... right 0.8 .... ... left 1.20 .... and I want to get the corresponding values of 'scale' in a new column

Dear useRs, Why are the rotated blue and yellow boxes in the example below clipped outside of 6 x 6 inch window in the middle of the page?? Where does the 6 x 6 inch window come from? I would like to make use of the entire page. > library(grid) > pdf(file = "FarmMaps.pdf", paper = "a4") > pushViewport(viewport( + width = unit(7.6, "inches"), height =