similar to: ANCOVA, Ops.factor, singular fit???

Dear R community members, I think I am asking a very simple question, but I really looked up in the faqs and manuals and found nothing helpful. I am trying to plot a data frame with the following structure (this is just a small extract): glo conc odor line series X1 X2 X3 X4 X5 X6 X7 X8 X9 X10 X11 X12 X13 1 0 AIR LN1 UP -0.488

Hi, I would like to convert my "character" sequences in my matrix/ data.frame into "numeric" where it is possible. I would also like to retain my alphabetic character strings in their original forms. "5.1" > 5.1 "hm" > "hm" k<-matrix(c("aa", "bb", 1,2, 4.3, 0), nrow=2) mode(k) <- "numeric" #

Hello, I am analyzing some climate time series data using the Mann Kendall package and was wondering if there was a way to calculate the trend using Sen's nonparametric estimator slope in R? Thank you in advance, Barry _________________________ Barry Baker, Ph.D. Global Climate Change Initiative The Nature Conservancy 2424 Spruce St., Suite 100 Boulder, CO 80302 Tel: (303)-541-0322 Fax:

I recently put Cent 5.2 (64 bit) on a new server using a Supermicro pdsbm-ln2+ sys board. I did the original installation at home using the 5.2 dvd I got via torrent. I turned it over to my NOC tech and it went right online so he ran yum update. With the most recent kernel, which went in with the update, the server hung on grub (after reboot). He did a fresh (minimal) Centos installation and once

Hello people I am doing some thinking about how to analyse data on dimorphic animals - where different individuals of the same species have rather different morphology. An example of this is that some male beetles have large horns and small wings, and rely on beating the other guys up to get access to mates, whereas others have smaller horns and larger wings, and rely on mobility to

Hello, I'm a bit new to the world of R so forgive my ignorance. I'm trying to do a zero-inflated negative binomial regression and have received an error message and i'm not sure what it means. I'm running R 2.5.1 on XP. I have just tried a really simple version of the model to see if it would run before I put all the variables in. I have attached all the variables to the

Objects compiled for the MS-ABI don't conform to it! Data types beyond 64 bit MUST BE returned by the callee via the hidden first argument allocated by the caller, NOT in XMM0! Demo/proof: from this source --- llvm-bug.c --- #ifndef __clang__ typedef struct { unsigned __int64 low; unsigned __int64 high; } __uint128_t; #else __attribute__((ms_abi)) #endif __uint128_t

We want to exclude virtio-gpu since it's irrelevant, large, and pulls in other unwanted dependencies (modeswitching, drm). Add a second list of kmods which is a blacklist, applied after the first. This reduces the libguestfs initrd size from 39M down to 17M, with concomitant small reductions in boot time. --- src/ext2_initrd.ml | 10 +++++++++- 1 file changed, 9 insertions(+), 1 deletion(-)

Eric, What do you think about renaming ‘src’ to ‘server’? I think it would help when newcomers navigate the source code. (And I hope that my FOSDEM talk will bring lots of new users and developers, hence why I've been working on this over the holiday.) If you agree then I'll push a commit which changes the directory name and makes the concomitant changes to makefiles, docs etc. Rich.

Hello, I am VERY new to R, just picking it up infact. I have got my head around the basics of ANOVA with post hoc tests but I am struggling with regression, especially with ANCOVAs. I have two sets of data, one of type A, one of type B. Both have been placed in a wind tunnel and sampled every week. The co variate is of course the days since the start. An example is day A B 0 10.0 10.0 7 9.0

I upgraded my Centos 4.7 server last night. Switched from a cheaper 50$ asus motherboard to a Supermicro motherboard. I also, using dd, copied entire 500g SATA seagate drive to new 500g SATA seagate drive so as to have two copies in case something went wrong. Anyway, now I keep getting this error: Nov 21 06:08:33 server kernel: hda: status timeout: status=0xd0 { Busy } Nov 21 06:08:33 server

> On Mon, 1 Apr 2019 21:49:06 +0000 (UTC) > Billy Bob via samba <samba at lists.samba.org> wrote: > > > > While 'make test' is intended to> pass generally, the reference > > > environment is Ubuntu 14.04 (soon to be> upgraded to 18.04 for the > > > next release).  > > > > By "next release," do you mean 4.10.1 or 4.11?

Could you please help me on the following ANCOVA issue? This is a part of my dataset: sampling dist h 1 wi 200 0.8687212 2 wi 200 0.8812909 3 wi 200 0.8267464 4 wi 0 0.8554508 5 wi 0 0.9506721 6 wi 0 0.8112781 7 wi 400 0.8687212 8 wi 400 0.8414646 9 wi 400 0.7601675 10 wi 900 0.6577048 11 wi 900

Hello, all. I've got what is probably a simple question about comparison of models using anova, specifically about the situations in which it's valid. I understand, I think, what's going on when the models are strictly nested (as most are in the demo(lm) examples). My question involves what happens when the models aren't strictly nested. In my particular case, I'm doing

Hello, I am loading a DBF file into R via JGR and am having trouble creating small multiple histograms on a date variable. Hist() handles the variable correctly. But I've been unable to work with lattice or ggplot2 despite trying format() and as.POSIXct(). Dates are in the format "2010-05-15" and the grouping variable is categorical. I'd appreciate it if someone would provide an

Thanks to John Fox, Brian Ripley, and Peter Dalgaard for responding. The short answer (as in Peter Dalgaard's reply, already posted to the list) is that the models I'm concerned with can in fact be compared using ancova. The key fact is that while the parameters may not be nested, the subspaces I'm examining are. An additional note from Prof. Ripley on AIC and BIC (which I quote in

Hello R experts I have two linear regressions for sexes (Male, Female, Unknown). All have a good correlation between body length (response variable) and head length (explanatory variable). I know it is not recommended, but for a good practical reason (the purpose of study is to find a single conversion factor from head length to body length), the regressions need to go through the origin (0

Chris you might know the answer to my HUUUUUUGE problem A few weeks ago you posted this message: "I have an ISDN PRI supplied by NTL (ex Diamond Cable, Nottingham) which is currently working happily with an SDX Index phone system. I have to replace this phone system shortly and I've been trying to get a * system working for some weeks now. I have configured the dial plan (which works)

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)

Hello, I am using the package "flexmix", specifically the function "stepFlexmix" and was hoping for some assistance: Here is my input: fit <- stepFlexmix(trips~.,data=data.frame(traveldata),k=1:5,nrep=5,model=FLXMRglm( family="gaussian")) And I recieve the following error message: *Error in FLXfit(model = model, concomitant = concomitant, control =