similar to: read.table or read.csv without row index?

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

Hi, I am trying to find an efficient way of applying a linear regression model to different factor combinations in a data frame. I want to obtain the output with minimal or no use of loops if possible. Please let me know if this query is unclear. Thanks, Murtaza

Dear R helpers,   Following is a R script I am using to run the Fast Fourier Transform. The csv files has 10 columns with titles m1, m2, m3 .....m10.     When I use the following commands, I am getting the required results. The probelm is if there are 100 columns, it is not wise to define 100 commands as fk <- ONS$mk and so on. Thus, I need some guidance to write the loop for the STEP A and

I am used to java (well, i dont remember it really well, but anyway) I have having a really difficult time making simple loops to work. I got the following to work: ## ##Creates objects Ux1, Ux2, Ux2 etc. that all contain n numbers in a random distribution ## m<-c(m1,m2,m3,m4,m5,m6,m7,m8,m9,m10)#these are defined as numbers (means) v<-c(v1,v2,v3,v4,v5,v6,v7,v8,v9,v10)#these

Hi! I am new to looping and R in general; and I have sent waaaay to much time on this one problem and am about a hair away from doing it manually for the next two days. So, there is a package that while calculating the statistic creates lists (that look like matrices) in the background. Each item (there are 10 items) has one of these ‘matrix looking list’ that I need to extract data from. The

Hi All, How do i calculate KMO for a dataset? *Dataset:---------------------* m1 m2 m3 m4 m5 m6 m7 m8 1 2 20 20 2 1 4 14 12 2 9 16 3 5 2 5 5 15 3 18 18 18 13 17 9 2 4 4 7 7 2 12 2 11 11 11 5 7 8 5 19 5 2 20 18 6 7 4 7 4 7 9 3 3 7 5 5 5 12 5 13 13 12 8 6 6 4 3 5 17 17 16 9 12 12 4 2 4 4 14 14 10 5 14

This email is also sent to cluster-devel at redhat.com. Since this issue is about both dlm and ocfs2, I send the email here to look for help from upstream. This is an already known issue. on ocfs2 with user space cluster stack, run the test script from http://people.redhat.com/~teigland/make_panic on the mounted ocfs2 volume from 2 nodes simultaneously, the access to ocfs2 volume on both nodes

Dear All I am reposting because I my problem is real issue and I have been working on this. I know this might be simple to those who know it ! Anyway I need help ! Let me clear my point. I have huge number of datapoints plotted using either base plot function or xyplot in lattice (I have preference to use lattice). name xvar p 1 M1 1 0.107983837 2 M2 11

Hi all! I?ve got some problems with the function gam (library mgcv). For some models I get the error message : Error: no valid set of coefficients has been found:please supply starting values In addition: Warning message: NaNs produced in: log(x) This is a shortened code I used: gam(y ~ M1 + M3 + M4 + M5 + M6 + sex + M1*M3 + s(age), family=Gamma(link ="identity"), weights=days) If

I have a question regarding significance testing for the difference in the ratio of means. The data consists of a control and a test group, each with and without treatment. I am interested in testing if the treatment has a significantly different effect (say, in terms of fold-activation) on the test group compared to the control. The form of the data with arbitrary n and not assuming equal

I ran the following R script under both Linux and Windows, and got 2 different results. Linux R version 2.7.1 and Windows R version 2.7.2. > library(FactoMineR) >x1=read.table("freqtest.txt",header=TRUE) >xrcc2=x1[,1:8] >p1=PCA(xrcc2, graph=FALSE) >p1$var freqtest.txt file lines of text : M1 M2 M3 M4 M5 M6 M7 M8 -1 -1 -1 -1 -1 -1 -1 -1 0 0 0 0 -1 -1 1 1 -1 -1 -1 -1 -1 -1

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 All: I am interested in multinomial logit models (function multinon, library nnet) but I'm having troubles in choose whether to define the predictors as factors or not. I had posted earlier this example (thanks for the reply ronggui): worms<- data.frame(year= rep(2000:2004, c(3,3,3,3,3)),age=rep(1:3,5),

On Tuesday 05 August 2008 12:39, Dan Gohman wrote: > On Tue, August 5, 2008 8:32 am, David Greene wrote: > > On Monday 04 August 2008 17:56, Dan Gohman wrote: > >> The applymask approach leverages use-def information rather than > >> what can be thought of as duplicating a subset of it, making the IR > > > > I don't understand what you mean by

On Tuesday 05 August 2008 13:27, David Greene wrote: > Neither solution eliminates the need for instcombine to be careful and > consult masks from time to time. > > Perhaps I'm totally missing something. Concrete examples would be helpful. Ok, so I took my own advice and thought about CSE and instcombine a bit. I wrote the code by hand in a sort of pseudo-llvm language, so

On Tue, August 5, 2008 8:32 am, David Greene wrote: > On Monday 04 August 2008 17:56, Dan Gohman wrote: >> The applymask approach leverages use-def information rather than >> what can be thought of as duplicating a subset of it, making the IR > > I don't understand what you mean by "duplicating" here. If you look just at the case where every instruction in a

Dear all, I am new to plotting Taylor Diagram using plotrix package within R, hence this post. I have written a script which plots Taylor Diagram with one reference and 7 model values. However the font size, line width and line type are not clear when saving the diagram as a jpeg file. I tried the functions lty, lwd and font but no apparent change. I am attaching the script here. Any help would

Background: OS: Linux Mandrake 10.1 release: R 2.0.0 editor: GNU Emacs 21.3.2 front-end: ESS 5.2.3 --------------------------------- Colleagues I am having some trouble extracting results from the function by, used to average variables in a data.frame first by one factor (depth) and then by a second factor (station). The real data.frame is quite large > dim(data.2001) [1] 32049 11 Here is a

Hi, May be this helps: m1<- as.matrix(read.table(text=" y1 g24 y1 0 1 g24 1 0 ",sep="",header=TRUE)) m2<-as.matrix(read.table(text="y1 c1 c2 l17 ?y1 0 1 1 1 ?c1 1 0 1 1 ?c2 1 1 0 1 ?l17 1 1 1 0",sep="",header=TRUE)) m3<- as.matrix(read.table(text="y1 h4??? s2???? s30 ?y1 0 1 1 1 ?h4 1 0 1 1 ?s2 1 1 0 1 ?s30 1 1 1

#I am trying to understand how R fits models for contrasts in a #simple one-way anova. This is an example, I am not stupid enough to want #to simultaneously apply all of these contrasts to real data. With a few #exceptions, the tests that I would compute by hand (or by other software) #will give the same t or F statistics. It is the contrast estimates that R produces #that I can't seem to