similar to: calculate multiple means of one vector

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 >

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

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

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 ##

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-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, 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 <-

http://www.nabble.com/file/p18018170/subdata.csv subdata.csv I've attached 100 rows of a data frame I am working with. I have one factor, id, with 27 levels. There are two columns of reference data, x and y (UTM coordinates), one column "date" in POSIXct format, and one column "diff" in times format (chron package). What I am trying to do is as follows: For each day

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

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

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

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

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

Hi all, I have a dataframe call "data", and have lots of rows. One of them is data$`birth` my data has been imported from an excel file in RSTUDIO I want to obtain in a function all rows (with the names) where data$`birth` is bigger than 1979/01/01 and extract in a excel file as an output (a sub-excel of the original). Can you guide with the functions I need to use? I have been many

Hi, I want to subset a data frame if one of the variables matches any in a list. I could of course do something like this: subset(dataset, var == 1 | var == 2 | var ==3) but that's tedious. I tried varlist = c(1,2,3,4) subset(dataset, any(var == varlist)) but it doesn't work because 'any' doesn't go row-by-row and hence always returns TRUE. Is there any simple way to do this?

I want to go through a column in data called date_abandoned....data["date_abandoned"]....and remove all the rows that have numbers greater than 1,010,000. The dates are in the format 20091114 so i'm just going to treat them as numbers for clean up purposes. I know that i use subset but not sure how to proceed from there. -- View this message in context:

I have a large dataset similar to this: ID time result A 1 5 A 2 2 A 3 1 A 4 1 A 5 1 A 6 2 A 7 3 A 8 4 B 1 3 B 2 2 B 3 4 B 4 6 B 5 8 I need to extract a number of features for each individual in it (identified by "ID"). These are: * The lowest result (the nadir) * The time of the nadir - but if the nadir level is present at >1 time point, I need the minimum and maximum time of nadir

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