similar to: Name collisions

I have a problem moving from multistratum aov analysis to lmer. My dataset has observations of ampl at 4 levels of gapf and 2 levels of bl on 6 subjects levels VP, with 2 replicates wg each, and is balanced. Here is the summary of this set with aov: >> summary(aov(ampl~gapf*bl+Error(VP/(bl*gapf)),hframe2)) > >Error: VP > Df Sum Sq Mean Sq F value Pr(>F) >Residuals

> On Jun 6, 2017, at 4:01 AM, Jim Lemon <drjimlemon at gmail.com> wrote: > > Hi Bogdan, > Kinda messy, but: > > N <- data.frame(N=c("n1","n2","n3","n4")) > M <- data.frame(M=c("m1","m2","m3","m4","m5")) > C <-

Hi there, I'm brand new to R, so let me know if this question is not appropriate for this list. I've been reading through the documentation and have tried a number of things, but am pretty much stuck so far. Here's the session info: > sessionInfo() R version 2.6.2 (2008-02-08) i386-apple-darwin8.10.1 locale: C attached base packages: [1] stats graphics grDevices

Thank you for your answers and suggestions! Well, I want to do some experiments about the compiler optimization in llvm under SPM and I need performance evaluation. As I know, alpha is a general-purpose CPU, so I consider that arm may be an alternative. Simplesim-arm is able to do performance simulation while m5-arm is still under development. Then, what should I do? Do the experiment under

Thank you David. Using xtabs operation simplifies the code very much, many thanks ;) On Tue, Jun 6, 2017 at 7:44 AM, David Winsemius <dwinsemius at comcast.net> wrote: > > > On Jun 6, 2017, at 4:01 AM, Jim Lemon <drjimlemon at gmail.com> wrote: > > > > Hi Bogdan, > > Kinda messy, but: > > > > N <-

Simple matrix indexing suffices without any fancier functionality. ## First convert M and N to character vectors -- which they should have been in the first place! M <- sort(as.character(M[,1])) N <- sort(as.character(N[,1])) ## This could be a one-liner, but I'll split it up for clarity. res <-matrix(NA, length(M),length(N),dimnames = list(M,N)) res[as.matrix(C[,2:1])] <-

Dear R users,I'm a new user of R. I'm trying to do a LM test an there is this type of error: Error in t(mX) %*% mX : requires numeric/complex matrix/vector arguments. To be clear I write down the code in which mY ( 126,1 ) mX (126,1) mZ(126,1) are matrix. LMTEST <- function(mY, mX, mZ)#mY, mX, mZ must be matrices!#returns the LM test statistic and the degree of freedom{iT =

Given four known and fixed vectors, x1,x2,x3,x4, I am trying to generate a fifth vector,z, with specified known and fixed partial correlations. How can I do this? In the past I have used the following (thanks to Greg Snow) to generate a fifth vector based on zero order correlations---however I'd like to modify it so that it can generate a fifth vector with specific partial

Here's another approach: N <- data.frame(N=c("n1","n2","n3","n4")) M <- data.frame(M=c("m1","m2","m3","m4","m5")) C <- data.frame(n=c("n1","n2","n3"), m=c("m1","m1","m3"), I=c(100,300,400)) # Rebuild the factors using M and N C$m <-

Hi all, I am new to LLVM (even the field of compiler) and currently I am engaged in the work of adapting LLVM IR to M5 simulator to observe the enhancement of the novel architecture we design. Simply speaking if you know little about M5, my aim is to know how LLVM IR is interpreted and encoded, then try to implement it in the framework of M5. I have read the LLVM documents, yet I still have some

Hi Bogdan, Kinda messy, but: N <- data.frame(N=c("n1","n2","n3","n4")) M <- data.frame(M=c("m1","m2","m3","m4","m5")) C <- data.frame(n=c("n1","n2","n3"), m=c("m1","m1","m3"), I=c(100,300,400))

NB: This email and its contents are subject to the Eskom Holdings Limited EMAIL LEGAL NOTICE which can be viewed at http://www.eskom.co.za/email_legalnotice ------------------------------------------------------------------------ Good Morning Im busy doing an exercise on Foundation of Statistical Description and Analysis,Please check the attached exercise on page 3.In this exercise the first

Hello list. I'm trying to rebuild the 2.6.9.67.0.20.EL kernel, but it fails even without modifications. How did I try it? Created a (non-root) build environment (not a mock ) Installed the kernel.scr.rpm and did a rpmbuild -ba --target=`uname -m` kernel-2.6.spec 2> prep-err.log | tee prep-out.log The build failed at the end: Processing files: kernel-xenU-devel-2.6.9-67.0.20.EL Checking

Dear R-helpers, I created an own function which looks like this s_elternmz <- function(Var="balt") { Dg_a<-mz[,c("asbhh","apkz",Var)] colnames(Dg_a)[colnames(Dg_a)=="apkz"]<-"bpkzm" colnames(Dg_a)[colnames(Dg_a)==Var]<-paste(Var,"_m",sep="")

I'm trying to select a subset of a dataframe while dropping some factors. While the dataset gets smaller all Factor levels remain and I need to get rid of them. Strangely enough, I am almost certain that the same code on the same data worked OK earlier today - and it is not the first time that I'm not able to replicate earlier results with this command (I know, I might just be going

Dear list members, I have got another problem. I imported an SPSS file with the Memisc package using the following commands: mz <- spss.system.file("myspssfile.sav") mz <- subset(mz,select=c( bsex,balt,xurb,dtaet,kartab,bgeb,boseit,bgeblan,xnuts2,kausb,xerwstat, asbper,asbhh,ajahr,aquartal,bstaat,xwieoft,gew1,apkz,bpkzm,bpkzv)) Afterwards I checked the measurements of the

Dear Bert, thank you for your response. here it is the piece of R code : given 3 data frames below --- N <- data.frame(N=c("n1","n2","n3","n4")) M <- data.frame(M=c("m1","m2","m3","m4","m5")) C <- data.frame(n=c("n1","n2","n3"),

Hi to all the people again, I was writting a simply function in R, and wish to collect the results in a excel file. The work goes as follows, Ciervos<-function(K1, K0, A, R,M,Pi,Hembras) {B<-(K1-K0)/A T1<-(R*Pi*Hembras-M*Pi+B)/(Pi-M*Pi+R*Pi*Hembras) P1<-Pi-B R1<-P1*Hembras*R M1<-P1*M T2<-(R1-M1+B)/(P1-M1+R1) P2<-P1-B R2<-P2*Hembras*R M2<-P2*M

Two questions related to creating animated movies with rgl: 1. I've created an rgl scene with 5 different views I want to display in a movie, but I'd like to insert pauses (say, 5 seconds) at each view. How can I do this? I first created 5 userMatrix's, then play3d( par3dinterp( userMatrix=list(M1, M2, M3, M4, M5)), ,duration=2*60/5) ) then tried simply repeating each twice,

Hello all, Probably my concepts about the data.frame and matrix and array in R are not clear, I need some clarification to help me understand them better. >M <- read.table("test1.csv",sep=",",row.names=NULL,header=T) gives me: M as M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 1 9 11 14 15 18 20 20 20 20 20 2 3 4 8 9 11 12 14 15 15 15 3 4 5 8 8 9 9 9 9 9 9 4 4