similar to: R syntaxe

Hi all, Let Names a vector of chatacters. For example, > Names [1] "g 604 be-0 -p1 (602 matches)" "g 606 Phli-0 -p2 (517 matches)" [3] "g 608 alu-0 (659 matches)" I try to use gsub or grep functions for two problems : 1. First, I would like to delete all the characters between parentheses. [1] "g 604 be-0 -p1" "g 606 be-0 -p2" [3] "g

Hi all, By default, the heatmap function gives an image with a dendrogram added to the left side and to the top. Is it possible to only add the dendrogram to the left side and let the order of the columns unchanged ? I tried heatmap(mat, col=rbg,Rowv=res.hclust$order,Colv=1:dim(mat)[[2]]). In this case, the order of the columns are unchanged but a dendrogram is added to the top. How can I

Hi ! I need a plot for data extending over several orders of magnitude on the y axis. The following command generates a nice looking semi-log plot for my data: plot(x,y,log="y",type="l",lty=3, ylim=c(0.01,2),yaxp=c(0.01,1,1),las=1) I would appreciate having also minor tick marks in-between the 3 major ticks obtained with the above command. The "minor.tick" function

Dear everyone, I am new in R and I've got difficulties in realizing the following tasks: -I have variables (factors) with different numbers of levels, either 1, 2 or 3. -I have a matrix containing these 204 factors and I have to correlate them by groups of 4 variables. -I have to delete the factors just having one level ( because when correlating one-level factors, the output is NA) here

Hi all, I want to conduct a cluster analysis with quantitative variables. More precisely, it concerns binary and non-ordered categorical variables. For such data, various similarity measures have been proposed, such as the Jaccard index or the simple matching index. So, is there a package such as mva or multiv in the case of quantitative variables? Could you indicate me reviews, papers or

Hi, I've been using R for a few weeks now, but consider myself still a newbie, especially in what concerns the basics of data handling in R. My situation is this: I read in data from a database using RODBC, and then use "table" to produce a table of "counts per years", table which I give to "plot". All is well, as long as there are no gaps in the years

Hi all, This is probably going to come off as unnecessary (and show my ignorance) but I am trying to understand the parameter estimates I am getting from R when doing an ANCOVA. Basically, I am accustomed to the estimate for the categorical variable being equivalent to the respective cell means minus the grand mean. I know is the case in JMP - all other estimates from these data match the

Hi A.K Regarding my question on comparing normal/ obese/overweight with blood pressure change, I did finally as per the first suggestion of stacking the data and creating a normal category . This only gives me a obese not obese 14, but when I did with the wide format hoping to get a obese14,normal14,overweight 14 Vs hibp 21, i could not complete any of the models. This time I classified obese=1

Hello! Can you help me? How to order an data.table by values of an column? Per example: Table no initial Categ Perc 468  31.52 351  27.52 0  0.77 234  22.55 117  15.99 table final Categ Perc 0  0.77 117  15.99 234  22.55 351  27.52 468  31.52 Lesandro Veja quais são os assuntos do momento no Yahoo! +Buscados [[alternative HTML version deleted]]

Hi R-users, I have a simple question for R heavy users. If I have a data frame like this dfr <- data.frame(id=1:16, categ=rep(LETTERS[1:4], 4), var3=c(8,7,6,6,5,4,5,4,3,4,3,2,3,2,1,1)) dfr <- dfr[order(dfr$categ),] and I want to score values or points in variable named "var3" following this kind of logic: 1. the highest value of var3 within category (variable named

Hi all, When I start R, it gives mkdir: Ne peut cr?er le r?pertoire `/home/mart/tmp/Rtmp11729'.: No such file or directory (I specify that my home path is /home/mart and the R version is 1.7.1) How I have to configure R to use the directory /tmp instead of /home/mart/tmp ? What is utility of this directory tmp for R? Thanks, Olivier

Hello, (Power Book G4, Mac OS X, R 2.5.0) I would like to repeat the function range for 85 Vectors (V1-V85). I tried with this code: i<-0 > repeat { + i<-i+1 + if (i<85) next + range (Vi, na.rm = TRUE) + if (i==85) break + } I presume that the Vi is wrong, because in this syntax i is not known as a variable. But I don´t know how to say that it is a variable here. Would be nice if

This is a question about removing the intercept in a binomial glm() model with categorical predictors. V&R (3rd Ed. Ch7) and Chambers & Hastie (1993) were very helpful but I wasn't sure I got all the answers. In a simplistic example suppose I want to explore how disability (3 levels, profound, severe, and mild) affects the dichotomized outcome. The glm1 model (see below) is

Hi all, Is there an equivalent to predict(...,type="linear") of a Proportional hazard model for a Cox model instead? For example, the Figure 13.12 in MASS (p384) is produced by: (aids.ps <- survreg(Surv(survtime + 0.9, status) ~ state + T.categ + pspline(age, df=6), data = Aidsp)) zz <- predict(aids.ps, data.frame(state = factor(rep("NSW", 83), levels =

Hi, I have a following data set: id event time (in sec) 1 add 1373502892 2 add 1373502972 3 delete 1373502995 4 view 1373503896 5 add 1373503996 ... I'd like to add new column "time on task" which is time elapsed between two events (id2 - id1...). What would be the best approach to do that? Thanks, Srecko [[alternative HTML

Hi! Does anyone know how to do the test for goodness of fit of a logistic model (in rms package) after running fit.mult.impute? I am using the rms and Hmisc packages to do a multiple imputation followed by a logistic regression model using lrm. Everything works fine until I try to run the test for goodness of fit: residuals(type=c("gof")) One needs to specify y=T and x=T in the fit. But

Dear R users, Basically, from the following arbitrary data set: a <- data.frame(id=c(c("A1","A2","A3","A4","A5"),c("A3","A2","A3","A4","A5")),loc=c("B1","B2","B3","B4","B5"),clm=c(rep(("General"),6),rep("Life",4))) > a

Dear developers, I have jutst started working with caret and all the nice features it offers. But I just encountered a problem: I am working with a dataset that include 4 predictor variables in Descr and a two-category outcome in Categ (codified as a factor). Everything was working fine I got the results, confussion matrix etc. BUT for obtaining the AUC and predicted probabilities I had to add

HI Elisa, You could use ?cut() vec1<-c(33,18,13,47,30,10,6,21,39,25,40,29,14,16,44,1,41,4,15,20,46,32,38,5,31,12,48,27,36,24,34,2,35,11,42,9,8,7,26,22,43,17,19,28,23,3,49,37,50,45) label1<-unlist(lapply(mapply(c,lapply(seq(0,45,5),function(x) x),lapply(seq(5,50,5),function(x) x),SIMPLIFY=FALSE),function(i) paste(i[1],"<x<=",i[2],sep="")))

I still need to do some repetitive statistical analysis on some outcomes from a dataset. Take the following as an example; id sex hiv age famsize bmi resprate 1 M Pos 23 2 16 15 2 F Neg 24 5 18 14 3 F Pos 56 14 23 24 4 F Pos 67 3 33 31 5 M Neg 34 2 21 23 I want to know if there are statistically detectable differences in all of the continuous variables in