similar to: Conditioned file Import?

I'm using R 1.6.2 on a Windows 2000 machine. I've plotted the results of an MDS run labeled by a numerical ID, and color coded by a group code: plot(cv.mds.spr$points, type="n", main="Non-Metric Multidimensional Scaling of SprRun CV Watersheds") text(cv.mds.spr$points, labels = as.character(cv.wshed.id.spr), col = codes(cv.wshed.grp), cex=.75) Question is, how do I

I'm using 1.6.2 on a win 2k box. (I know I'm due for an upgrade.) I've used brute force to label a series of vectors, and I'm wondering if there's a better way to do this. I wanted to create a biplot of the 2nd & 3rd PCs, and did this: test <- edit(loadings(cv.prc.spr)) test.1 <- test[,1] test.2 <- test[,2] test.3 <- test[,3] x0 <- 0 y0 <- 0 i <-

Easy question that I can't find an answer for. I'm trying to subset a data frame and want to exclude the positive values, i.e. I want the NA values. My data: > summary(temp$tuna) Min. 1st Qu. Median Mean 3rd Qu. Max. NA's 1 2 3 3 4 5 1211 Querying for subset(temp, tuna %in% "NA", select.... subset(temp, tuna == NA,

This isn't an R issue per se, but given the recent issues with Mozilla and help.search(), I figured I'd float it. I use mozilla on a WIN2000 box. I was using 1.0 and the help.search() wasn't working as has been discussed over the past few days. Yesterday I upgraded to 1.1, and the javascript help still does not work. (I checked and it is enabled.) Another problem I noticed this morning

Does the polymars library exist anymore? I see reference to it at http://rweb.stat.umn.edu/R/doc/html/packages.html, but not on CRAN (looked in contrib and contrib/Old). -- Rob Schick Ecologist NOAA Fisheries Santa Cruz Lab 110 Shaffer Road Santa Cruz, CA 95060 Phone: 831.420.3960 -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read

I have a dataframe that I'm trying to reshape, and need advice. My data: > klam.merge[200:225,] stream lulc x sumlength pct.lgth 200 1223030419685 92 0.25000000 9.89 2.52780586 201 1223030419686 23 0.00274154 4.73 0.05796068 202 1223030419686 41 0.75009917 4.73 15.85833341 203 1223030419686 42 2.65000000 4.73 56.02536998 204

I have a data set of monthly river flows from 1960-2000, which are similar in structure to the nottem data: > klam.flow Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep 1961 1461 1716 2524 1773 1906 2005 1756 1575 1387 983 1094 1382 1962 1907 2253 1985 1907 1769 1676 2634 1386 929 766 968 1309 ... I tried plotting with > ts.plot(klam.flow) Which quickly led me to

I have a 30 x 27 data frame, which I'm trying to scale and transform. Only I want to scale certain all variables except one (the dependent, which I want to log+1 transform). I can use split() and then scale() and log1p(), but I'm wondering if I can do this in one call. I tried apply(), but I could only get the whole data frame, not a part of it: > test <- apply(chin.sub, 2, log1p)

Hi all, I'm running into some computer issues when trying to run a binomial model for spatially correlated data using glmmPQL and was wondering if anyone could help me out. My whole dataset consists of about 300,000 points for which I have a suite of environmental variables (I'm trying to come up with a habitat model for a species of seal, using real (presence) and simulated dives

Hello All - Any recommendations or suggestions for neat ways to visualize data taken from a 3-axis accelerometer? My study species is aquatic, so I would be interested in movement in the 3 dimensions in addition to being able to incorporate the time series as well. Is there a package in R that might be useful for this? Thank you in advance, Jen ~~~~~~~~~~~~~~~~~~~~~ Jennifer Maresh, PhD

Hi all, I am analyzing data on habitat utilization of seals in the Southern Ocean. My data show spatial autocorrelation, which I'm interested in incorporating into my model. I am trying to model the presence of dives (versus simulated pseudo-absences) using a binomial generalized binomial model (glmmPQL), since I can incorporate the autocorrelation structure to the model using that package.

I am trying to do a Nonparametric Tukey-type multiple comparison post-hoc test to determine which groups are significantly different. I have read the dialogue on this topic from the R-help, and am still not clear why no statistical packages include this test as an option? Is it not an appropriate test to conduct on non-normally distributed data? Is the only option to calculate it by hand

I don't use R much, and I have been unable to figure out how to get the subset of my data frame that I would like. For example, if this were my data frame: > dfr <- data.frame(x=rep(letters[1:3], 4), y=(1:12), z=(LETTERS[1:12])) > dfr x y z 1 a 1 A 2 b 2 B 3 c 3 C 4 a 4 D 5 b 5 E 6 c 6 F 7 a 7 G 8 b 8 H 9 c 9 I 10 a 10 J 11 b 11 K 12 c 12 L I would like to

# Hi there, # I am trying to apply a function over a moving-window for a large number of multivariate time-series that are grouped in a nested set of factors. I have spent a few days searching for solutions with no luck, so any suggestions are much appreciated. # The data I have are for the abundance dynamics of multiple species observed in multiple fixed plots at multiple sites. (I total I

The following should work: > dfr.samp <- dfr[tapply(1:nrow(dfr), dfr$x, sample, 1),] > dfr.samp x y z 10 a 10 J 2 b 2 B 9 c 9 I Andy From: Kelly Hildner > > I don't use R much, and I have been unable to figure out how > to get the > subset of my data frame that I would like. > > For example, if this were my data frame: > > > dfr <-

http://bugzilla.mindrot.org/show_bug.cgi?id=667 Summary: Openssh 3.7x, Windows ssh clients and Ldap don't play together Product: Portable OpenSSH Version: 3.7.1p1 Platform: ix86 OS/Version: Linux Status: NEW Severity: critical Priority: P2 Component: PAM support AssignedTo:

Hello - I am attempting to add interaction terms to a model using the gamm function in the mgcv package. I stripped it down to only two terms to simplify it. I have no trouble with individual terms, continuous or factors, nor with interacting factor terms; I cannot, however, figure out how to add interactions between continuous*factor terms. I applied a smoother to my continuous term because it

Hi- I am interested in running the BCP model in R and I am also new to R. My main issue is how to ask a specific questions within the script for this model, i.e., how one or multiple dependent factors (blue) are interact with the dependent factor (yellow), and nest the question do categorical factors (green) changes those interactions. I have attached some fake data in the link below with

Hi- I''m a complete newbie trying to install R and the ''tree'' package on a linux box. I installed R successfully using an RPM for Redhat 6.2. I downloaded the tree*.gz file, ran tar, the fired up R. When I''m at the >prompt in R, and type ''R INSTALL /usr/apps/tree'' I get: ''Error: Syntax error'' I want tree to end up in the

Hi All: I am running prcomp on a very large array, roughly [500000, 3650]. The array itself is 16GB. I am running on a Unix machine and am running ?top? at the same time and am quite surprised to see that the application memory usage is 76GB. I have the ?tol? set very high (.8) so that it should only pull out a few components. I am surprised at this memory usage because prcomp uses the SVD