similar to: pair matching

Aloha all, I love using ggplot. It took a while to get used to the grammar of graphics, but it is starting to get easy now that I am thinking in a more structured way. A question. I'm making a wind rose that I'd like to be oriented with due north straight up. I've discovered that the orientation is sensitive to how north is represented. When north is represented as 0,

Aloha all, I have a data frame with 4 columns. The first three are factors (f1, f2, f3) and the fourth is numeric. I'd like to explore these data using median polish. To do that I plan to use medpolish() on the matrix[f1,f2xf3], then medpolish on the resulting matrix[f2,f3]. This approach is described by Cook on page 141 of Exploring Data Tables, Trends, and Shapes. split()

Aloha all, I have an adjacency matrix for an acyclic digraph that contains transitive relations, e.g. (u,v), (v,w), (u,w). I want a DAG with only intransitive relations. Can someone point me to an R function that will take my adjacency matrix and give me back one with only intransitive relations? In the example, I'd like to get rid of (u,w) and keep (u,v) and (v,w). All the best, Tom --

This message is in MIME format. The first part should be readable text, while the remaining parts are likely unreadable without MIME-aware tools. Send mail to mime@docserver.cac.washington.edu for more info. --1465796871-645734172-974620647=:18687 Content-Type: TEXT/PLAIN; charset=US-ASCII Hi all, I've discovered and (hopefully) fixed a bug in the stars function I wrote some time ago.

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Hi all, Please let me know if this isn't the correct place to report bugs in contributed code. Otherwise, the following code contains one additional line and a short comment above it. The extra line of code catches the unusual situation where a data column contains all 0 values. The corrected code is below the signature. Thanks for your help. Tom Thomas S. Dye, Ph.D.

Aloha all, I know too little about what I'm about to write and hope I'm not wasting your time. For a class I'm teaching in archaeological data analysis, I'm trying to put together a routine that calculates the so-called Petersen index and, especially, confidence intervals for the index. This was introduced to archaeologists by N.R.J. Fieller and A. Turner in an article

Hello R-users, I am currently trying to learn how to use the function gls of the nlme library. I fitted the following model: Generalized least squares fit by REML Model: response ~ array + dye + genes + variety + variety * genes + array * genes + dye * genes Data: data I have 11 arrays, 2 dyes, 2 varieties, 3200 genes, and 2 replications for each. Therefore I should have the corresponding

Hi all, when i run this script: >read.table("Angelika.txt",header=T,sep="\t") >mytable=read.table("Angelika.txt",header=T,sep="\t") >for ( dye in c("A","B","C","F","G","K","L","M")) + { + for (cond in 1:8) + { + measurement =

I had need of a bit of computer archeology (oddly enough, for a couple of archaeologists, but that's another story). I used Henry Bartlett' HABit Wordstar Converter (version 3) (http://www.hotkey.net.au/~hambar/habit/wsconvrm.htm) to convert some Wordstar for Mess-DOS files to text and HTML. It worked just fine under wine (http://www.winehq.org). wine-20041201-1fc3winehq on Fedora Core 3

Hi, I have the following linear mixed model: y(g,i,j,k,l)=u + L(g) + T(i) + D(j) + S(k) + (TS)(i,k) + error(g,i,j,k,l) where S(k) and the combined effect (TS)(i,k) are random effects whereas the rest are fixed effects. How do I specifiy the random part of the model formula in lme(), especially concerning the combined effect (TS)? Moreover, when I run the model as a fixed effect model I get

Hi, I am a student in archaeology with some interest in statistics and R. Recently I've obtained the permission to distribute in the public domain a small dataset (named "spearheads" with 40 obs. of 14 variables) that was used in an introductory statistics book for archaeologists (published in 1994). I've rewritten most of the exercises of that book in R and made them

I am a novice R user, and have been in trouble to get the right mixed model syntax in microarray analyses. There are three factors: Dye(2 levels), Temperature(3 levels) and Array(3 for each Temperature with a total of 9 arrays). I want to treat array as random, and to regard array variation different between Temperatures. So the model I want to seek is: Y = Dye + Temp + Dye + Temp*Dye +

Hello all, I have data: Genes time rep vart dye y trt 130911 sa1-d07 030min 1 col g 9.636244 o 145771 sa1-d07 030min 1 col r 8.107577 c 93335 sa1-d07 030min 1 ler g 7.409566 o 94821 sa1-d07 030min 1 ler r 5.107160 c 10119101 sa1-d07 030min 2 col g 8.336862 o 11605101 sa1-d07 030min 2 col r 7.824530 c 725313 sa1-d07

Dear R helpers, I am working with R 2.4.1 GUI 1.18 (4038) for MacOSX. I have a matrix of 10 000 genes and try to run the following commands: > model.mix<-makeModel (data=data, formula=~Dye+Array+Sample+Time, random=~Array+Sample) > anova.mix<-fitmaanova (data, model.mix) > test.mix<-matest (data, model=model.mix, term="Time", n.perm=100, test.method=c(1,0,1,1))

Guys can you tell me if a samba 4 DC implements any kerberos polices. am wanting to extend our kerberos ticket expiry values to 24hours is this possible ? -- Damien Dye IT Manager *Sondrel Ltd* Sondrel House, Theale Lakes Business Park Moulden Way, Sulhamstead, Berkshire, RG7 4GB, UK Tel: +44(0)118 9838 550 www.sondrel.com [image: Sondrel] <http://www.sondrel.com/> This e-mail and

Guys is it possible on samba 4 to raise the expiry time on tgt tickets to be more than 10 hours ? I have users running scripts that need a longer expiry time on the token on another side note is it the Samba 4 DC that decides the renewal date of the tokens also ? Regards -- Damien Dye IT Manager *Sondrel Ltd* Sondrel House, Theale Lakes Business Park Moulden Way, Sulhamstead, Berkshire,

Dear all, I have a performance problem in terms of computing time. I estimate mixed models on a fairly large number of subgroups (10000) using lme(.) within the by(.) function and it takes hours to do the calculation on a fast notebook under Windows. I suspect by(.) to be a poor implementation for doing individual analysis on subgroups. Is there an alternative and more efficient way for doing

Does anyone have nice quality controlls for affy arrays,.... Can't find any tools as are being used for 2 dye arrays..... cheers, marinus This e-mail and its contents are subject to the DISCLAIMER at http://www.tno.nl/disclaimer/email.html [[alternative HTML version deleted]]

Hello, I use lme4 package. library(lme4) fit=lmer(y ~ time+dye+trt+trt:time + (1|rep), data=dataset, na.action='na.omit') anova(fit) The anova gives sequential F-tests and sequential SS. My question is: how I can get partial F-tests and partial SS? For lm (not lmer) anova(lm(y~x+z)) we can use anova(fit, ssType=3) but it is not work for lmer. Natalia.