similar to: Select part of character row name in a data frame

Quoting Francesca PANCOTTO <f.pancotto at unimore.it>: > Dear R contributors, > > I have a problem in selecting in an efficient way, rows of a data > frame according to a condition, > which is a part of a row name of the table. > > The data frame is made of 64 rows and 2 columns, but the row names > are very long but I need to select them according to a small

(Re-)read the discussion of indexing (both `[` and `[[`) and be sure to get clear on the difference between matrices and data frames in the Introduction to R document that comes with R. There are many ways to create numeric vectors, character vectors, and logical vectors that can then be used as indexes, including the straightforward way: df[ c( "Unique to strat ", "Unique

Thanks a lot, so simple so efficient! I will study more the grep command I did not know. Thanks! Francesca Pancotto > Il giorno 19 ott 2017, alle ore 12:12, Enrico Schumann <es at enricoschumann.net> ha scritto: > > df[grep("strat", row.names(df)), ] [[alternative HTML version deleted]]

Dear contributors I have tried this experiment: x<-c() for (i in 1:12){ x[i]<-list(cbind(x1[i],x2[i])) #this is a list of 12 couples of time series I am using to perform a test } # that compares them 2 by 2 # ################# #trace statistic test<-data.frame() cval<-array( , dim=c(2,3,12)) for (i in 2:12){ for (k in 1:2){ for (j in 1:3){ result[k,j,i]<-

Dear Contributors, I have an easy question for you which is puzzling me instead. I am running loops similar to the following: for (i in c(100,1000,10000)){ print((mean(i))) #var<-var(rnorm(i,0,1)) } This is what I obtain: [1] 100 [1] 1000 [1] 10000 In this case I ask the software to print out the result, but I would like to store it in an object. I have tried a second loop, because if I

I apologize, I solved the problem, sorry for that. f. Il giorno gio 13 giu 2024 alle ore 16:42 Francesca PANCOTTO < francesca.pancotto at unimore.it> ha scritto: > Dear Contributors > I am trying to create a numeric series with repeated numbers, not > difficult task, but I do not seem to find an efficient way. > > This is my solution > > blocB <- c(rep(x = 1,

Maybe this was your solution? blocC <- c(rep(x=c(1:13), times=84)) blocC <- arrange(.data = data.frame(blocC), blocC) The second line sorts, but that may not be needed depending on application. The object class is also different in the sorted solution. Tim -----Original Message----- From: R-help <r-help-bounces at r-project.org> On Behalf Of Francesca PANCOTTO via R-help Sent:

Dear Contributors, thanks for collaboration. I am trying to reorganize data frame, that looks like this: n1.Index Date PX_LAST n2.Index Date.1 PX_LAST.1 n3.Index Date.2 PX_LAST.2 1 NA 04/02/07 1.34 NA 04/02/07 1.36 NA 04/02/07 1.33 2 NA 04/09/07 1.34 NA 04/09/07

Dear Contributors I am trying to create a numeric series with repeated numbers, not difficult task, but I do not seem to find an efficient way. This is my solution blocB <- c(rep(x = 1, times = 84), rep(x = 2, times = 84), rep(x = 3, times = 84), rep(x = 4, times = 84), rep(x = 5, times = 84), rep(x = 6, times = 84), rep(x = 7, times = 84), rep(x = 8, times = 84), rep(x = 9, times = 84),

Dear Contributors, I am asking help on the way how to solve a problem related to loops for that I always get confused with. I would like to perform the following procedure in a compact way. Consider that p is a matrix composed of 100 rows and three columns. I need to calculate the sum over some rows of each column separately, as follows: fa1<-(colSums(p[1:25,])) fa2<-(colSums(p[26:50,]))

Dear Contributors, I am trying to perform a simulation over sample data, but I need to reproduce the same simulation over 4 groups of data. My ability with for loop is null, in particular related to dimensions as I always get, no matter what I try, "number of items to replace is not a multiple of replacement length" This is what I intend to do: replicate this operation for four

OS X R 4.3.3 Colleagues I have created objects using the Surv function in the survival package: > FIT.1 Call: survfit(formula = FORMULA1) n events median 0.95LCL 0.95UCL SUBDATA$ARM=1, SUBDATA[, EXP.STRAT]=0 18 13 345 156 NA SUBDATA$ARM=2, SUBDATA[, EXP.STRAT]=1 13 5 NA 186 NA SUBDATA$ARM=2, SUBDATA[, EXP.STRAT]=2 5

Hi Dennis, look at the help page for summary.survfit, the Value n.event. G?ran On 2024-05-15 22:41, Dennis Fisher wrote: > OS X > R 4.3.3 > > Colleagues > > I have created objects using the Surv function in the survival package: >> FIT.1 > Call: survfit(formula = FORMULA1) > > n events median 0.95LCL 0.95UCL >

Terry - your example didn't demonstrate the problem because the variable that interacted with strata (zed) was not a factor variable. But I had stated the problem incorrectly. It's not that there are too many strata terms; there are too many non-strata terms when the variable interacting with the stratification factor is a factor variable. Here is a simple example, where I have

Terry - your example didn't demonstrate the problem because the variable that interacted with strata (zed) was not a factor variable. But I had stated the problem incorrectly. It's not that there are too many strata terms; there are too many non-strata terms when the variable interacting with the stratification factor is a factor variable. Here is a simple example, where I have

Terry Therneau has been very helpful on r-help but we can't figure out what change in R in the past months made extra columns appear in model.matrix when the terms object is subsetted to remove stratification factors in a Cox model. Terry has changed his logic in the survival package to avoid this issue but he requires generating a larger design matrix then dropping columns. A simple

Dear all, I'm using R 2.8.1 under Windows Vista on a dual core 2,4 GhZ with 4 GB of RAM. I'm trying to reproduce a result out of "Analysis of Financial Time Series" by Ruey Tsay. In R I'm using the fGarch library. After fitting a ar(3)-garch(1,1)-model > model<-garchFit(~arma(3,0)+garch(1,1), analyse) I'm saving the results via > result<-model

Dear Contributors, I hope someone has found a similar issue. I have this data set, cp1 cp2 role groupid 1 10 13 4 5 2 5 10 3 1 3 7 7 4 6 4 10 4 2 7 5 5 8 3 2 6 8 7 4 4 7 8 8 4 7 8 10 15 3 3 9 15 10 2 2 10 5 5 2 4 11 20 20 2 5 12 9 11 3 6 13 10 13 4 3 14 12 6 4 2 15 7 4 4 1 16 10 0 3 7 17 20 15 3 8 18 10 7 3 4 19 8 13 3 5 20 10 9 2 6 I need to to average of groups, using the values of column

Dear Contributors I have a problem with the collection of data from the results of a test. I need to perform a comparative test over groups of data , recall the value of the pvalue and create a table. My problem is in the way to replicate the analysis over and over again over subsets of data according to a condition. I have this database, called y: gg t1 t2 d 40 1 1

Dear Contributors I would like to perform this operation using a loop, instead of repeating the same operation many times. The numbers from 1 to 4 related to different groups that are in the database and for which I have the same data. x<-c(1,3,7) datiP1 <- datiP[datiP$city ==1,x]; datiP2 <- datiP[datiP$city ==2,x]; datiP3 <- datiP[datiP$city ==3,x] datiP4 <-