similar to: help with hier.part

All, I'm having a problem selecting directly from a vector. I've written ways to do this indirectly, but I'd rather do it directly and didn't see this in the manual. Essentially, I have: > group.label.new [1] 7 9 6 1 10 4 8 3 2 5 > junk [1] 1 2 > group.label.new[junk && 8:10] [1] 7 9 6 1 10 4 8 3 2 5 I'd like to select the elements

Hi, I have no experience with R and I'm finding the manuals a bit obtuse and written as if I already understood R. I'm trying to import a csv file from a floppy and it's not working. The code I'm using is read.table("F:\GEORGIA\species_richness\SR_use.csv", sep=",", header = TRUE, row.names = 1) I'm assuming that this command is case sensitive so

Hi. I'm trying to plot the ratio of used versus unused bird houses (coded 1 or 0) versus a continuous environmental gradient (proportion of urban cover [purban2]) that I would like to convert into bins (0 - 0.25, 0.26 - 0.5, 0.51 - 0.75, 0.76 - 1.0) and I'm not having much luck figuring this out. I ran a logistic regression and purban2 ends up driving the probability of a box being

Dear R-users, I did some more research and I'm still not sure how to set up an ANCOVA with nestedness. Specifically I'm not sure how to express chicks nested within boxes. I will be getting Pinheiro & Bates (Mixed Effects Models in S and S-Plus) but it will not arrive for another two weeks from our interlibrary loan. The goal is to determine if there are urbanization (purban)

I just had a manuscript returned with the biggest problem being the analysis. Instead of using principal components in a regression I've been asked to analyze a few variables separately. So that's what I'm doing. I pulled a feather from young birds and we quantified certain aspects of the color of those feathers. Since I often have more than one sample from a nest, I thought I

Hi. I'm attempting to fit a logistic/binomial model so I can determine the influence of landscape on the probability that a box gets used by a bird. I've looked at a few sources (MASS text, Dalgaard, Fox and google) and the examples are almost always based on tabular predictor variables. My data, however are not. I'm not sure if that is the source of the problems or not because the

R-users, I'm having some trouble getting .glm and glm.nb to run a polynomial. I've used x*x and x^2 and neither works. I've checked out the archives and they refer to an archive that's no longer working. I've seen that they use poly() but I'm following up my analysis with cv.glm so I'd prefer to keep using glm. It's easier to just add a column to my data but

Dear R-users, I set up an experiment where I put up bluebird boxes across an urbanization gradient. I monitored these boxes and at some point I pulled a feather from a chick and a friend used spectral properties (rtot, a continuous var) to index chick health. There is an effect of sex that I would like to include but how would I set up a regression and look at the effect of urbanization

Hi. Is there a way to get the values predicted from (leave-one-out) cv.glm? It seems like a useful diagnostic to plot observed vs. predicted values. Thanks, Jeff **************************************** Jeffrey A. Stratford, Ph.D. Postdoctoral Associate 331 Funchess Hall Department of Biological Sciences Auburn University Auburn, AL 36849 334-329-9198 FAX 334-844-9234

Folks, Thanks for the help with the hier.part analysis. All the problems stemmed from an import problem which was solved with file.chose(). Now that I have the variables that I'd like to use I need to run some GLM models. I think I have that part under control but I'd like to use a jackknife approach to model validation (I was using a hold out sample but this seems to have fallen out

Hi, Last week my class conducted an experiment by putting out clay caterpillars to look at the effects of urbanization, color, and location on caterpillar predation. There were two sites (urban, rural), three colors (green, yellow, red) and two locations at each site (edge, interior). The entire data set is below. I've checked out the MASS book, Dalgaard's book, and the R-help archives

Hi folks, I am running a very simple regression using mylm <- lm(mass ~ tarsus, na.action=na.exclude) I would like the use the residuals from this analysis for more regression but I'm running into a snag when I try cbind(mylm$residuals, mydata) # where my data is the original data set The error tells me that it cannot use cbind because the length of mylm$residuals is

Hi everyone, I determined the presence of three types parasites in a passerine bird over two years. I would like to create a bar chart that shows the proportion infected on the y and year/parasite on the x such that each type of parasite is grouped together (single label) and a bar for each year . This would show if there have been changes in the prevalence of a the parasite over two years.

Hi everyone, I've been asked to run a number of Wilcoxon tests on some behavioral data (below is a sample). They want me to compare each trial to the first trial, considered the control trial. I know I can use brackets to index and select, for example, trial 1 vs. trial 4 (not exactly sure how to set that up either) but it would save me a ton of time if there was a way to do all the

Hi everyone, I'm looking to produce a side-by-side histogram of the number of trips taken by jays with a particular number of acorns after accounting for year (year "one" and year "two"). I know this involves indexing first then creating a histogram but I'm not sure how I'd do this. I want to explore the possibilities that jays are altering their strategies in

Hi everyone, I've been asked to run a number of Wilcoxon tests on some behavioral data (below is a sample). They want me to compare each trial to the first trial, considered the control trial. I know I can use brackets to index and select, for example, trial 1 vs. trial 4 (not exactly sure how to set that up either) but it would save me a ton of time if there was a way to do all the

I've been trying for a couple of weeks to get FreeBSD + winbindd + PAM working, without success. I'm hoping that someone here has bumped into my problem before and has some advice to give. My current setup is winbindd from Samba 2.8.8a on both FreeBSD 4.8-RELEASE and 5.1-BETA. I've configured Samba with the following options: syslog, nocups, utmp, msdfs, quota, recycle, audit,

Hi everyone, A beguinner question. - How shall i import 9 different ascii (created from a gis layer (arcmap grid)) into R to create a single dataframe for using in hier.part? Should i use read.table, then turn each created object into a single vector using unlist and finally use data.frame to joint all the vectors into a unique data frame (xcan in the usage of hier.part) ? I´ve been trying to

Hello R-team I´ve got a question concerning the hierarchical partitioning function. If the variables of a model fitted with glm (binomial)show a high joint effect, does this necessarily only mean, that these variables are highly correlated and therefor the model fitting was not optimal, or can it also be, that a high joint contribution means, that the relevant variables only show there full

I am using the hier.part package for calculating the goodness of fit. Before I started with my data I tried to use the example that the package comes with . I have loaded the library hier.part and gtools. But the package gives the following error Loading required package: gregmisc Loading required package: gregmisc Warning messages: 1: There is no package called 'gregmisc' in: