similar to: Problem loading packages in R 2.13.0 on Mac

I am trying to tweak how my categorical x-axis labels are formatted in my bar graph. Specifically, I would like to a) decrease the spacing between lines (e.g. spacing between Dialium and guianensis) b) right justify the text and c) have each species name align with the center of the corresponding bar graph. A simplified version of my code thus far is as follows. I am using RStudio v.

I am making a barplot using barplot2 from gplots where each bar represents a specific tree species. I have formatted the species names on the x-axis so that the genus name is above the species name and have then rotated the labels 45 degrees to save room. This is my code: >columncolor<-c("grey20", "grey20", "grey20", "grey70",

I am making a barplot using barplot2 from gplots and would like to format the names of my categorical variables (tree species) on the x- axis so that the genus name is above the species name (to save room). My code so far is: speciesnames<-c("Dialium guianensis", "Inga alba", "Tachigali versicolor", "Brosimum utile", "Caryocar

Hi, I have a data frame with columns as follows: tree species (independent variable) and several dependent variables (e.g. carbon, nitrogen, phosphorus). Each row represents one tree sample. Some tree samples are unique species in the data frame while other species were replicated (i.e. rows 1,2,3 may be identical for the "tree species" column but have different values for the

Is there code in R to automatically assign letters to different groups that are found to be statistically significant using a post-hoc test following an ANOVA? For example, let's say I found that relative rates of tree growth were statistically significant between tree species using an ANOVA and then I ran a TukeyHSD post-hoc test to determine which species were statistically

Listmates, I have had a few boxes where the 'matchname' message is filling my syslog with one new message ever ~40 seconds or so. No performance problems, just the log annoyance. An example of the messages are: Jan 11 13:43:03 nemesis smbd[2246]: [2010/01/11 13:43:03, 0] lib/util_sock.c:1685(get_peer_name) Jan 11 13:43:03 nemesis smbd[2246]: Matchname failed on Adrienne-PC.rbpllc.com

To all, I'm working with code below to produce a map with station data plotted in points, but right now I'm having trouble with the mapping portion of this code states <- data.frame(map("state", plot=FALSE,xlim= c(-85,-75),ylim=c(33,37))[c("x","y")]) usamap<- ggplot(states)+geom_path(aes(x,y)) usamap When I plot this the problem is that the bounds of

Greetings! I'm having an issue with the windrose produced by the windrose function from the circular package. For our weather stations in North Carolina I'm helping with a script which takes hourly wind speed and direction data to create windroses for our end users. One of the stations in the mountains frequently reaches wind speed of 40 to 60 mph and in storms can reach wind speed over

Hello: I am trying to use optim() to estimate the maximum likelihood of a function a*x^b = y. Unfortunately, I always get the error, that there is no default value for b. Could you give me an example, on how to correctly optimize this function with input data x<-c(1,3,11,14). Thanks a lot, Adrienne -- *********************************************************************** Adrienne

Hi, All: Is there a way to identify whether any users are using a particular package in a shared network R installation? I ask, because we have such a multiple-user installation and when I tried to install a package using Rgui that was in use by Rterm on a single-user installation, 'install.packages' deleted the existing package but failed to install the new version;

Hi, Thank you for the tip. I tried to re-intall R from Debian "stable", in which R's version is 1.4.0. And the installation of "mvtnorm" works. I then re-installed R yet again from Debian "unstable" (woody), in which R's version is 1.5.1. The installation of "mvtnorm" fails again with the same error message. Another package that failed with the

Folks, I'm a bit puzzled by the fact that if I generate 100,000 standard normal variates using rnorm() and perform the Jarque-Bera on the resulting vector, I get p-values that vary drastically from run to run. Is this expected? Surely the p-val should be close to 1 for each test? Are 100,000 variates sufficient for this test? Or is it that rnorm() is not a robust random number generator?

Hi, There's probably some simple way of doing this, but I'm just not seeing it - How do I get the background to be white instead of grey when I have a cloud plot (using the lattices package)? par(bg="white") isn't working. I'm assuming par commands won't work on lattice plots. What should I use instead? Thanks, Adrienne [[alternative HTML version deleted]]

Something might have slipped by me, but I got into the following situation installing Rcmdr: < install.packages("Rcmdr",depend=TRUE) > Oodles of Output, until: * Installing *source* package 'multcomp' ... ** R ** data ** inst ** preparing package for lazy loading Error in dyn.load(x, as.logical(local), as.logical(now)) : unable to load shared library

(this after asking the package author) Hi I cannot install the rmvnorm package under R-2.3.0, or R-2.3.1 beta. It installs fine under R-2.2.1. transcript for installation under R-2.3.0 follows. Robin-Hankins-Computer:~/scratch% R --version R version 2.3.0 (2006-04-24) Copyright (C) 2006 R Development Core Team R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to

Hi all, I've been trying to install the "mvtnorm" package (in a Linux R version) without sucess. I write install.packages("mvtnorm",lib="/home/posmae/cnaber",repos="http://cran.uk.r-project.org/") and the following message arises ================================================== downloaded 160Kb * Installing *source* package 'mvtnorm'

R-listers, I have noticed several posts on issues with difftime producing NA's but they have been for older versions of R. Here's the issue associated with difftime that I am dealing with in R 2.12.2. > preciptime = strptime("01/10/2007 14:00",format="%m/%d/%Y %H:%M") > class(preciptime) [1] "POSIXlt" "POSIXt" > # Now using difftime, this

Hi, If I have two sets of directional data (in radians) and want to compare them with a multifactorial anova. Is it even legitimate to compare circular data with an anova? The books I've picked up from the library don't really say, but it looks unlikely. If it is allowable, is my having stored the data as circular (X = as.circular(A)) something the aov() function will take into account,

Greetings all, Ran into a strange problem with the krige function from geoR. The problem that I am having is that while the krige function seems to work well, the resulting predicted values are all NAs. Given the size of the datasets I am working with can't attach it, but I can provide snippets of the datasets. > casedata station year month day obs mpe bias type

All, I'm working with ggplot2 to produce some graphics that will be part of my master's thesis. Here's what I would like to do here, (attached is an example of how far I've gotten). I'm working on mapping the values of several different parameters for each station in my study. So far I've been working with scale_color_gradientn to handle the coloring. What I would like