similar to: How to label specific points on a scatterplot

I noticed today that in R 2.3.1, I get > serialize(list(1,2,3), NULL, ascii = TRUE) [1] "A\n2\n131841\n131840\n19\n3\n14\n1\n1\n14\n1\n2\n14\n1\n3\n" > but in R 2.4.0 alpha I get > serialize(list(1,2,3), NULL, ascii = TRUE) [1] 41 0a 32 0a 31 33 32 30 39 36 0a 31 33 31 38 34 30 0a 31 39 0a 33 0a 31 34 [26] 0a 31 0a 31 0a 31 34 0a 31 0a 32 0a 31 34 0a 31 0a 33 0a >

Hello, I am struggling to find the root of a exponent function. "uniroot" is complaining about a values at end points not of opposite sign? s<- sapply(1:length(w),function(i) + { + + + + + uniroot(saeqn,lower=-5000,upper=0.01036597923,l=list(t=w[i],gp=gp))$root + }) Error in uniroot(saeqn, lower = -5000, upper = 0.01036597923, l = list(t = w[i], : f() values at

http://bugs.freedesktop.org/show_bug.cgi?id=25966 Summary: nv25 : rxvt scrolling is very slow Product: xorg Version: 7.5 Platform: x86 (IA32) OS/Version: Linux (All) Status: NEW Severity: normal Priority: medium Component: Driver/nouveau AssignedTo: nouveau at lists.freedesktop.org

Hi, I wonder if anybody could help me in converting this easy SAS program into R. (I'm still trying to do that!) PROC IMPORT OUT= WORK.CHLA_italian DATAFILE= "C:\Documents and Settings\carleal\My Documents\REBECCA\stat\sas\All&nutrients.xls" DBMS=EXCEL2000 REPLACE; GETNAMES=YES; RUN; data chla_italian; set chla_italian;

Hi there, I hope I can get advice regarding the calculation of leverage values or studentized residual values of a non-linear regression model. It seems like rstudent() does not work on a nls object. Many thanks in advance! Best regards, Xingli

I am using the Unix version of R (version 1.7.0), installed via fink on a G4 Macintosh. I recently upgraded from version 1.6.0 and found that the "car" library now has a problem: ---Begin transcript--- >library(car) Attaching package 'car': The following object(s) are masked from package:base : dfbeta dfbeta.lm dfbetas dfbetas.lm hatvalues hatvalues.lm

Hi, I am trying to figure out how to get the correlation coefficient for a QQ plot (residual plot). So to be more precise, I am creating the plot like this: qq.plot(rstudent(regrname), main = rformula, col=1) But want to also access (or compute) the correlation coefficient for that plot. Thanks, Tom [[alternative HTML version deleted]]

Dear users, I'm using rpart for classification trees, but my code isn't working when I try to use all the variables in my data frame. This data frame was created from a data frame with 1775 variables, but I choose only 13. arv13<-rpart(iv~.,data=gn,method="class",parms=list(split="information")) #Error: Error in `[.data.frame`(frame, predictors) : undefined

I'm trying to sort a DATAFRAME by a column "ID" that contains alphanumeric data. Specifically,"ID" contains integers all preceeded by the character "g" as in: g1, g6, g3, g19, g100, g2, g39 I am using the following code: DATAFRAME=DATAFRAME[order(DATAFRAME1$ID),] and was hoping it would sort the dataframe by ID in the following manner g1, g2, g3, g6, g19,

I just started using R last week. I have a dataset with 3 columns - Plate, Well and Raw I need to make a simple plot(Well~Raw) but only when Plate = 101 Thanks for your help. -- View this message in context: http://r.789695.n4.nabble.com/Simple-conditional-plot-tp3654300p3654300.html Sent from the R help mailing list archive at Nabble.com.

An embedded and charset-unspecified text was scrubbed... Name: nem el?rhet? URL: <https://stat.ethz.ch/pipermail/r-help/attachments/20110420/4913654b/attachment.pl>

I am working on a function that will remove outliers for regression analysis. I am stating that a data point is an outlier if its studentized residual is above or below 3 and -3, respectively. The code below is what i have thus far for the function x = c(1:20) y = c(1,3,4,2,5,6,18,8,10,8,11,13,14,14,15,85,17,19,19,20) data1 = data.frame(x,y) rm.outliers =

Hi I am not sure if this issue has been resolved, but on the latest opus 1.1.4, * I downloaded the tarball, * ran ./configure followed by * make and then * make check Can you please help? Thank you make[3]: Entering directory `/prj/avspw/karthikr/Development/BFamily/Broadcast/SDM845/Opus/opus-1.1.4/doc' doxygen Warning: ignoring unsupported tag

A colleague was asking me if R does multi-level modelling as opposed to multiple regression. Since I have no knowledge of multi-level modelling (except 5 minutes googling ) I thought that I would as here. Does are offer any multi-level modeling packages? It looked like arm might be one but I was not sure. Thanks

Dear Colleagues, I have a dataframe with variables: [1] "ID" "category" "a11" "a12" "a13" "a21" [7] "a22" "a23" "a31" "a32" "b11" "b12" [13] "b13" "b21"

I'm trying to impute data using the mi package, but after running through almost the entire first round of imputations (which takes quite a while), it throws this error (I'll include the whole output prior to the error for context). Does anyone know what is causing it, or how I can fix it? More specifically, how can I tell what is throwing the error so I know what to fix? Is

Hi, I must be doing something silly here, because I can't get the studentised and standardised residuals from r output of a linear model to agree with what I think they should be from equation form. Thanks in advance, Jennifer x = seq(1,10) y = x + rnorm(10) mod = lm(y~x) rstandard(mod) residuals(mod)/(summary(mod)$sigma) rstudent(mod)

Sorry, I am sure, this must be documented somewhere (but there are that many docs and tutorials to scan for topics..., actually a great thing... but if you are in a hurry..): I want to save a plot as .ps (or .eps): > postscript("plot1.eps", horizontal=FALSE, onefile=FALSE,height=8,width=8,pointsize=10) > plot(hpfit$fit,rstudent(hpfit),xlab="Fitted

Hi all, I'm trying to apply loess regression to my data and then use the fitted model to get the *standardized/studentized residuals. I understood that for linear regression (lm) there are functions to do that:* * * fit1 = lm(y~x) stdres.fit1 = rstandard(fit1) studres.fit1 = rstudent(fit1) I was wondering if there is an equally simple way to get the standardized/studentized residuals for a

Dear community, I'm having this silly problem. I've a linear model. After fixing it, I wanted to know which data had studentized residuals larger than 3, so i tried this: d1 <- cooks.distance(lmmodel) r <- sqrt(abs(rstandard(lmmodel))) rstu <- abs(rstudent(lmmodel)) a <- cbind( mydata, d1, r,rstu) alargerthan3 <- a[rstu >3, ] And suddenly a[rstu >3, ] has