similar to: Advanced Filtering problem

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 >

Dear R-users, I have written the following code to generate some trellis plots. It works perfectly fine except that it is quite slow when it is apply to my typical datasets (over several thousands of lines). I believe the problem comes from the loops I am using to subset my data.frame. I read in the archives that the tapply function is often more efficient than a loop in R. Unfortunately ,

Hi folks, I created a subset of a dataframe (i.e., selected only men): subdata <- subset(data,data$gender==1) After a residual diagnostic of a regression analysis, I detected three outliers: linmod <- lm(y ~ x, data=subdata) plot(linmod) Say, the cases 11,22, and 33 were outliers. Here comes the problem: When I want to exclude these three cases in a further regression analysis, - for

Dear all, First, let's create some data to play around: set.seed(1) (df <- data.frame(Group=rep(c("Group1","Group2","Group3"), each=10), Value=c(rexp(10, 1), rexp(10, 4), rexp(10, 10)))[sample(1:30,30),]) ## Now we need the empirical distribution function: edf <- function(x) ecdf(x)(x) # empirical distribution function evaluated at x ##

Hello all, I'm trying to get a subset of a data frame by taking all rows where the 2nd column is >= Min and <= Max. I can do that by a 2 step process similar to the following: subData <- dataFrame[dataFrame[,2] >= Min,] subData2 <- subData[subData[,2] <= Max,] Then I try to graph the results where col 2 is the X var and col 3 is the Y var. Therefore I do the following: X

Hi, I am trying to create a googleVis motion chart with monthly data. When formatting the date column as a Date class variable, the plot as presented in the browser becomes considerably slower and very prone to crashing the browser. To illustrate this issue I have modified the WorldBank demo. ### objects from demo("WorldBank", package = "googleVis") M <-

Dear list, this must be an easy one: I have a data.frame of two columns, "ID" with four different levels (A to D) and numerical "size", and each of the 4 different IDs is repeated a different number of times. I would like to get the mean size for each ID as another data.frame. I have tried the following: >ID= as.character(unique(data[,1])) # I use unique() because

Dear R experts, I got help to build a loop but there is a bug inside it that causes one part of the mechanism to fail. It should grow once, but if keep growing on rows where $ti_all is not NA. Here is a wall of code that very crudely demonstrates the problem, there is a couple of dim() outputs at the end where you can see how it the second time around keeps adds (2) rows, but this does not

Dear R Users, I recently posted an email on this list about the use of data.frame and overlaying multiple plots. Deepayan kindly indicated to me the panel.superposition command which worked perfectly in the context of the example I gave. I'd like to go a little bit further on this topic using a more complex dataset structure (actually the one I want to work on). >mydata Plot

I am creating a timeline plot, but running into a problem in positions where the values to plot are too close together to print the text without overlap. The simplest way I can think of to solve this (although there may be other ways?) is to create a new numeric vector whose values are as close as possible to the original vector, but spread out to a given minimum difference. For example, take

Hello R users, I'm wondering whether it is possible to manage big data set in R? I have a data set with 3 million rows and 3 columns (X,Y,Z), where X is the group id. For each X, I need to run 2 regression on the submatrix. I used the function "split": datamatrix<-read.csv("datas.csv", header=F, sep=",") dim(datamatrix) # [1] 2980523 3

Help! I am a new R user. It has been slow getting up to speed, but definitely rewarding. I have come up against a problem I can't handle. I would very much appreciate any help. I am writing a vector auto regression (VAR) function that utilizes existing R statistical functions. I would like to use the step function to do step-wise elimination on each univariate time series model. No

https://bugs.freedesktop.org/show_bug.cgi?id=99354 Bug ID: 99354 Summary: [G71] "Assertion `bkref' failed" reproducible with glmark2 Product: Mesa Version: 13.0 Hardware: x86 (IA32) OS: Linux (All) Status: NEW Severity: normal Priority: medium

Hi everybody, I am beginer in R and I need your precious help. I want to create a small function in R as in sas to retrieve date. I have a file with data that import in R. DATE PAYS nb_pays.ILI. 1 24/04/2009 usa 0 2 24/04/2009 usa 0 3 24/04/2009 Mexique 0 4 24/04/2009

Hello, I'm having problems working with date values in POSIXct format. Here is what I got (eg.lig attached): x <- read.table("eg.txt", sep = ',', col.names=c("ok","time","secs","lig")) # it gives time as factor z <- cbind(x,colsplit(x$time, split="\\s", names=c("date", "clock")))

Dear R-Users, I have the following two vectors: data <- rnorm(40, 0, 2) positions <- c(3, 4, 5, 8, 9, 10, 20, 21, 22, 30, 31, 32) now I would like to calculate the mean of every chunk of data-points (of the data-vector) as defined by the positions-vector. So I would like to get a vector with the mean of element 3 to 5 of the data-vector, 8 to 10, 20 to 22 and so

Hello, I'm creating a loop to work with vegan, to get a species abundance curve. Here I send the script I've created and also an excel file to prove what it can do. Well, I have a database with 20 years, and each year we have sampled 19 stratum, and in each estratum we have carry out some sumpling. Then, with the script that I've sent I've got to calculate the species abundance

Description of what I am trying to do: I am using the xyplot code below to plot the variable ?MeanBxg? against the variable ?PercentVarExplained? for all 9 possible combinations of variables ?bdg? and ?bdx?. Within each of these 9 scenarios I am plotting a separate line for each of up to 9 different methods that I used to estimate the variable MeanBxg. These methods are identified by the numeric

I've tagged a release for libdrm 2.4.23 principally to expose the new kernel parameters for BLT support on SandyBridge and relaxed fencing which are needed to build the next release of xf86-video-intel. However, I'm lacking sufficient privileges to actually upload the tarballs myself at the moment, so you'll have to make do with the git tag! -Chris Adam Jackson (1):