[R] creating bins for a plot

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

[R] nontabular logistic regression

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

Re: [R] nontabular logistic regression

University Auburn, AL 36849 334-329-9198 FAX 334-844-9234 http://www.auburn.edu/~stratja Gavin Simpson [EMAIL PROTECTED] 10/13/06 11:23 AM On Fri, 2006-10-13 at 09:28 -0500, Jeffrey Stratford wrote: Hi. I'm attempting to fit a logistic/binomial model so I can

[R] glm with nesting

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

Re: [R] glm with nesting

(julian). But | does indicate grouping not nested, correct? Could someone suggest some coding that might work? Thanks again, Jeff Peter Dalgaard [EMAIL PROTECTED] 10/05/06 7:14 AM Jeffrey Stratford [EMAIL PROTECTED] writes: I just had a manuscript returned with the biggest problem being

Re: [R] glm with nesting

Harold and list, I've changed a few things since the last time so I'm really starting from scratch. I start with bbmale - read.csv(c:\\eabl\\2004\\feathers\\male_feathers2.csv, header=TRUE) box -factor(box) chick - factor(chick) Here's a sample of the data

[R] 3-dimensional table

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

Re: [R] nested ANCOVA: still confused

for box such as: rtot.lme - lme(fixed=rtot~sexv, random=~purban2|box, na.action=na.omit,bb) or in lmer lmer(rtot ~ sexv + (purban|box), bb, na.action=na.omit) Harold -Original Message- From: Jeffrey Stratford [mailto:[EMAIL PROTECTED] Sent: Tue 1/24/2006 8:57 PM To: Doran

[R] nested ANCOVA: still confused

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

Re: [R] nested ANCOVA: still confused

models in the Matrix package, you would do lmer(rtot~sex + (purban|box:chick) + (purban|box), na.action=na.omit, data=bb) Hope this helps. Harold -Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Jeffrey Stratford Sent: Tuesday, January 24, 2006 11:34 AM

[R] regression with nestedness

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

[R] cv.glm help: no responses?

I sent out a question a few days ago asking help with cv.glm and I didn't get any responses. Is it my question? I'd appreciate any response just to see my post makes it out there. What I'm looking to do is to get a column of predicted responses from cv.glm (leave-one-out). This produces a

[R] predicted values from cv.glm

Hi folks, Is there a way to get the predicted values from leave-one-out cross validation using cv.glm? More generally, is there a way to see what output is available with any function that may not show up using the help() function? Below is the code that I've been using: SRCOUNT -

[R] predicted values from cv.glm

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

[R] cv.glm help

I would appreciate some help writing R code to plot predicted species richness vs. observed species richness (nat_est) with 95% CI lines. I'm using glm to get model coefficients and remove-one cross validation to get predicted (cv.glm). Here is what I have for the code so far: SRCOUNT -

[R] glm x^2

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

[R] Poisson/negbin followed by jackknife

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

[R] index question

Thanks for those on the list that answered my previous question. I'm just about where I need to be (looking at output). In the hier.part documentation there is a line env - urbanwq[,2:8]. This means use rows 2 through 8 in the data frame urbanwq, right? What does the comma represent? If

[R] help with hier.part

R-users, Attached is the file (SR_use2.txt) I'd like to include and includes column headers. nat_est is the response variable and is the number of species at a particular point. The other variables are the explanatory vars (vark, var2, var1, UK, U2, U1, GK, G2, G1, PK, P2, P1). Here is

[R] Import help (neophyte)

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)