similar to: R package classification

Hi, I'm trying to install RSPython v0.5-4 on a debian machine (woody, testing) but am having the following problem. $R CMD INSTALL -c --library=/usr/lib/R/library RSPython_0.5-4.tar.gz 2>err But then... $python >> import RS Error in .PythonInit() : Error in Python call: values Error in library("RSPython") : .First.lib failed for 'RSPython' Traceback (most recent

Dear list, If anyone knows how to assign dimnames to matrices or arrays I would be most grateful for help. I've tried various permutations of likely-looking code but get error messages every time. I could find no example in the documentation. Many thanks, Dan Bebber Department of Plant Sciences University of Oxford South Parks Road Oxford OX1 3RB UK Tel. 01865 275000

I have spatial data on a sphere (the Earth) for which I would like to run an gls model assuming that the errors are autcorrelated, i.e. including a corSpatial correlation in the model specification. In this case the distance metric should be calculated on the sphere, therefore metric = "euclidean" in (for example) corSpher would be incorrect. I would be grateful for help on how to

Some notes on installing rgeos in R 2.14.0 on a Linux Mint 11 (x86_64-pc-linux-gnu) machine 1. rgeos 0.1-15 will not run with GEOS 3.2.0-1, which is the version currently available on Synaptic package manager 2. I installed GEOS 3.3.1 (the latest version) from http://trac.osgeo.org/geos/, but rgeos will not run with this either 3. I then install GEOS 3.2.3, and now rgeos works fine! It seems

Dear R list I have an m * n matrix P and a vector V of length n containing indices for rows in P. For each of the m columns I want to extract the value in the row specified by V, and put these values into a new vector W of length n. At present I am doing this with a for.... loop, but I imagine there is a faster way that doesn?t involve loops. If anyone knows the way I would be most grateful.

Hello, My data are numbers of trees in plots sampled in a number of forest stands. Some stands were subjected to a treatment, others not. Several plots were sampled per stand to get a better idea of what the stand means were, but replication is really at the stand level. Therefore I think this is a split-plot design. I would like to know whether the treatment affected the number of trees, so:

I would like to extract predicted failure times from a coxph model in library(survival). However, none of the prediction options ("lp", "risk", "expected", "terms") seem to bear any relationship to failure time. Perhaps I am asking the wrong question, but can coxph provide predicted failure times? Thanks, Dan Bebber Department of Plant Sciences University

Hello, when I try to use the filled circle (pch = 16) in a Windows metafile, it appears highly pixelated rather than as a smooth vector. The other filled circles (pch = 19 and 20) are vector circles, filled with pixels. Results are the same whether I use windows() and save or copy as a metafile, or win.metafile() Also, some of the other symbols are misshapen, e.g. the diamond pch = 23 is not

Hello, I've just located the illuminating explanation by Douglas Bates on degrees of freedom in mixed models. The take-home message appears to be: don't trust the p-values from lme. Questions: Should I give up hypothesis testing for fixed effects terms in mixed models? Has my time spent reading Pinheiro & Bates been in vain? Is there a publication on this issue? Thanks, Dan Bebber

I am plotting subsets of my data, using ylim. This works fine, but the outer margin line widths of the plot are thin, due to clipping. If I include > trellis.par.set(clip=list(panel = "off")) then the outer margin line widths are fine, but the outlying data is visible. Is there any way of achieving both correct margin line widths and clipping of outlying data? Thanks, Dan Bebber

Do any of you know any simple programming editors for R scripts which offer basic colour-coding and bracket-matching facilities? Dregging through scripts to find a missing comma or parentheses is something I'd rather do less of... Jon Minton [[alternative HTML version deleted]]

Dear R list: I modelled changes in a variable (mconc) over time (d) for individuals (replicate) given one of three treatments (treatment) using: mconc.lme <- lme(mconc~treatment*poly(d,2), random=~poly(d,2)|replicate, data=my.data) summary(mconc.lme) shows that the linear coefficient of one of the treatments is significantly different to zero, viz. Value Std.Error

I have obtained shapefiles for Indian states from here: http://www.maptell.com/index.php?option=com_remository&Itemid=159&func=fileinfo&filecatid=115&parent=category Problem: I want to extract centroid coordinates for each State, but there is some coding problem with the shapefiles that prevents this. #Code: #After extracting the shapefiles from the india_state.zip file, then:

Hello, I am having trouble specifying a suitable nlme model. My data structure is described by gd <- groupedData(ppath ~ lcut | exp, outer = ~ bait, inner = ~ weight, data = d) i.e. the response (ppath) of several subjects (sub) was measured at levels of a continuous variable (lcut). Subjects were given either of one level of a factor (bait), and all subjects were measured at two levels

Is there a package, or does anyone have code they are willing to share, that would allow me to simulate sampling of dead wood pieces across an area? I am specifically looking for code to simulate the dead wood distribution as small line segments across an extent, and then I will "sample" the dead wood using different sampling techniques including line transects, fixed area plots, etc.

Hello, I wrote a wrapper for symbols() that produces a bivariate bubble plot, for use when plot(x,y) hides multiple occurrences of the same x,y combination (e.g. if x,y are integers). Circle area ~ counts per bin, and circle size is controlled by 'scale'. Question: how can I automatically make the smallest circle the same size as a standard plot character, rather than having to

Hi, I am trying to download data from Bloomberg through R. If I try to download intraday data for multiple tickers and only one field, I get the error, written below in red. How do I get rid of this error? > dat<-blpGetData(conn, c("NOK1V FH Equity","AUA AV Equity"), "LAST_PRICE",

glm(S ~ -1 + Mdif, family=quasipoisson(link=identity), start=strt, sdat) gives error: > Error in glm.fit(x = X, y = Y, weights = weights, start = start, etastart > = > etastart, : > cannot find valid starting values: please specify some strt is set to be the coefficient for a similar fit glm(S ~ -1 + I(Mdif + 1),... i.e. (Mdif + 1) is a vector similar to Mdif. The error

Hello, I have a model glm(Y ~ X, family = quasipoisson(link = "identity")) I would like to vary the coefficient for X and observe the effect on the deviance. Is this possible? Many thanks, Dan Bebber Department of Plant Sciences University of Oxford

Could someone please give a brief explanation, or pointer to an explanation, of the following error: > arima(ts.growth, order = c(1,0,0),include.mean=T) Error in arima(ts.growth, order = c(1, 0, 0), include.mean = T) : non-stationary AR part from CSS and why it does not arise with > arima0(ts.growth, order = c(1,0,0)) Many thanks ____________________________ Dr. Daniel P. Bebber