similar to: how to delete a matrix column

I have a dataset like this: p aa index x y z sdx sdy sdz delta as ms cur sc 1 821p MET 1 -5.09688 32.8830 -5.857620 1.478200 1.73998 0.825778 13.7883 126.91 92.37 -0.1320180 111.0990 2 821p THR 2 -4.07357 28.6881 -4.838430 0.597674 1.37860 1.165780 13.7207 64.09 50.72 -0.0977129 98.5319 3 821p GLU 3 -5.86733 30.4759

if I want to put fig1plot to the left, figYPplot to the right figYAaplot on the bottom. How to modify the following cod to do these? \begin{figure}[H] \centering \begin{minipage}[t]{0.5\textwidth} \centering <<label=fig1plot,fig=TRUE,echo=FALSE>>= <<fig1plot>> @ %\caption{Caption 1} \end{minipage} \begin{minipage}[t]{0.5\textwidth} \centering

I have a data(ABC) like this: x y A 3 4 A 1 3 B 2 6 B 4 8 C 5 4 C 6 7 I want to split this data into A: x y A 3 4 A 1 3 B B 2 6 B 4 8 C C 5 4 C 6 7 anyone knows how to do that? thanks, Aimin Yan

I have a question in R. In directory H:/Delta_angle I have 19 files like this: ALA.delta ASN.delta ASP.delta CYS.delta GLN.delta GLU.delta HIS.delta ILE.delta LEU.delta LYS.delta MET.delta PHE.delta PRO.delta SER.delta THR.delta TRP.delta TYR.delta VAL.delta I want to read these files to 19 data sets in R. All these data sets have "P","AA",index","delta"

Hello, I use nnet to do prediction for a continuous variable. after that, I calculate correlation coefficient between predicted value and real observation. I run my code(see following) several time, but I get different correlation coefficient each time. Anyone know why? In addition, How to calculate prediction accuracy for prediction of continuous variable? Aimin thanks, > m.nn.omega

I try Sweave and get Sweave-test-1.tex but hot to run LaTeX on 'Sweave-test-1.tex'? I am using WinEdt. thanks, Aimin > Sweave(testfile) Writing to file Sweave-test-1.tex Processing code chunks ... 1 : print term verbatim 2 : term hide 3 : echo print term verbatim 4 : term verbatim 5 : echo term verbatim 6 : echo term verbatim eps pdf 7 : echo term verbatim eps pdf

I am trying to fit a logistic regression model for this data set. Firstly, I want to plot P(Y=1) vs As and P(Y=1) vs Aa. Does any body know how to do these in R. Thanks, Aimin > p5 <- read.csv("http://www.public.iastate.edu/~aiminy/data/p_5_2.csv") > str(p5) 'data.frame': 1030 obs. of 6 variables: $ P : Factor w/ 5 levels "821p","8ABP",..: 1

I have a data set like this I want to assign "outward" to Y if sc <90 and assign "inward" to Y if sc>=90. then cbind(p1982,Y) to get like these p aa as ms cur sc Y 1 154l_aa ARG 152.04 108.83 -0.1020140 92.10410 inward 2 154l_aa THR 15.86 28.32 0.2563560 103.67100 inward 3 154l_aa ASP 65.13 59.16 0.0312137 7.27311 outward 4 154l_aa CYS 57.20 49.85

Dear R list, I have a question in R, it could be very simple, but I don't know how to do it? for example: I assign 6 to x in beginning of of my R script code > x<-6 ...... After many line code, I forget using x variable before, I use x again, and do assignment like this > x<-45 > x [1] 45 then value 6 of previous x is replaced by 45. I am wondering if there are some way R

I run the following code, all other is ok, but plot(m.svm,p5.new,As~Cur) is not ok Anyone know why? install.packages("e1071") library(e1071) library(MASS) p5 <- read.csv("http://www.public.iastate.edu/~aiminy/data/p_5_2.csv") p5.new<-subset(p5,select=-Ms) p5.new$Y<-factor(p5.new$Y) levels(p5.new$Y) <- list(Out=c(1), In=c(0)) attach(p5.new)

How to add mean,sd, number of observation in each panel for lattice histogram? Aimin

In order to start matlab server in R , I using the following commands getwd() setwd("D:\R_matlab") install.packages("R.oo") install.packages("R.matlab") install.packages("R.utils") library(R.matlab) Matlab$startServer() a minimized MATLAB Command Window come out, but I can't make this window become larger. Does anyone know why? I type

Dear All, I am working with linear mixed-effects models using the lme4 package in R. I created a model with the lmer function including some main effects, a two-way interaction and a random effect. Now I am searching for a way to save the predicted values for this model. As far as I can see, there is no command in lme4 to save the predicted values (like the predict(model) function in e.g.

Does anyone know how to solve this question about R.matlab? I am in windowsXP, my matlab is matlab 7.0.0 19920(R14) thanks, Aimin > matlab <- Matlab(host="localhost", port=9998) > if (!open(matlab)) throw("Matlab server is not running: waited 30 seconds.") Error in list("throw("Matlab server is not running: waited 30 seconds.")" =

How can I best achieve the following (works in Splus): filenames <- dos("dir *.sasb7dat /b") What I am asking, more generically, is: how can I capture the output of a DOS command in R? I have tried using system("COMMAND.COM /c dir /b", intern=T, show.output.on.console=T) where intern: a logical, indicates whether to make the output of the command an R

Hi, I just encountered a problem in R that may easily be fixed: If one uses attach for a data.frame e.g. 10000 times and forgets detach, then R gets incredibly slow (less then 10% of the original speed). My system: platform powerpc-apple-darwin6.0 arch powerpc os darwin6.0 system powerpc, darwin6.0 status major 1 minor 6.1 year 2002

I draw dotplot using the following code: sd.dotplot<-dotplot(data.47.nmr$om_sd ~ as.factor(data.47.nmr$position) |as.factor(data.47.nmr$pr), data = data.47.nmr,layout=c(1,1), xlab="Position", xlim=range(data.47.nmr$position),ylab="Sd", main="Changes of omega angle in different positions", scales = list(x = list(rot = 45))) However I get same xlim for each

consider p as random effect with 5 levels, what is difference between these two models? > p5.random.p <- lmer(Y ~p+(1|p),data=p5,family=binomial,control=list(usePQL=FALSE,msV=1)) > p5.random.p1 <- lmer(Y ~1+(1|p),data=p5,family=binomial,control=list(usePQL=FALSE,msV=1)) in addtion, I try these two models, it seems they are same. what is the difference between these two model. Is

(If this only happens in Win 98, I'm sure I could live with it. Just may be helpful to report it, I hope.) Start up R GUI, then > plot(1:4,1:4) # then close manually by clicking X > plot(1:4,1:4) # ditto > methods(plot) sometimes produces normal output and even the following prompt, but then crashes immediately, or more often, crashes immediately with no output. I can do any

bug.report() tells me to email to r-bugs@r-project.org, whereas the Web site http://www.r-project.org/ points me to r-bugs@biostat.ku.dk. Which should I believe? Simon Fear Senior Statistician Syne qua non Ltd Tel: +44 (0) 1379 644449 Fax: +44 (0) 1379 644445 email: Simon.Fear@synequanon.com web: http://www.synequanon.com Number of attachments included with this message: 0 This