similar to: read.table but more tables at once

Hello, I need a command. I have a lot of data in different dataframes(auto.0a, auto.0b, auto.0c, auto.5Na,...), that has similar names. I could print the names all at once wih a loop with the command paste(), see below:

Dear R commnuity, Thanks a lot for your help. I want to read in tables, the problem is that the table is composed in a difficult way. In ariginal it looks like this: 669 736 842101610481029114711811166124312081128117611221026 9581024 992 685 720 829 925 995 96010241057116611501104106410711092 983 908 989 904 924 896 882 897 909 933 928 907 916 902 546 734 784 868 970 954

dear R-community, Is it possible to have one pie chart of a large radius and then a pie chart with smaller radius placed on top of the larger so the centers of the two pie charts coincide? I managed to place a filled circle with smaller radius in the piechart, see below. Thanks in advance, Sybille pie(rep(1,12), col=rainbow(24), radius=0.9, labels=

Hello everyone, I would like to test two regression slopes:do they differ significantly?The data and commands I've used so far: x<-8.5:32.5 #Vektor x y<-c( NA , NA , 5.67 , 6.53 , 6.83, 7.41 , 7.93 , 8.5 , 8.86, 9.46 , 9.82 , 10 ,10.35 , 10.7 ,11.03 ,11.37 ,11.61 ,11.84, 12.12, 12.39 ,12.67 ,12.96, 13.28 ,13.47, 13.65) #Vektor y (regression<-lm(y~x)) summary(regression)

Hello, I want to make a contour plot. I have a matrix (nrow=4,ncol=58) . and two lists, one with 4 values (the depths) and one with 58 values (time in days)( Depth (should be later on the y-axis),and Time(should be later on the x-axis)) In the matrix there is the temperature for a specified depth and time. there are missing values (NAs). I also put ranges for x-,y-,zlim. I

Hello, I would like to get a correlation coefficient (R-squared) for my model. I don't know how to calculate it in R. What I've done so far: x<-8.5:32.5 #Vektor x y<-c(NA ,5.88 , 6.95 , 7.2 , 7.66 , 8.02 , 8.44 , 9.06, 9.65, 10.22 , 10.63 ,11.06, 11.37, 11.91 ,12.28, 12.69 ,13.07 , 13.5 , 13.3 ,14.14 , NA , NA , NA , NA , NA) #Vektor y

>>>>> Martin Maechler >>>>> on Tue, 8 Sep 2020 10:40:24 +0200 writes: >>>>> Hugh Parsonage >>>>> on Tue, 8 Sep 2020 18:08:11 +1000 writes: >> I can only reproduce on Windows, but reliably (both 4.0.0 and 4.0.2): >> $> R --vanilla >> x <- c(0L, -2e9:2e9) >> # > Segmentation

hi everyone, i have a problem with a function that i defined: the function needs to use a function which is defined outside the function but i realised that this is not working. a friend told me that this must be a problem with hidden parameters. a workaround works when i just define all parameters instead of using the function itself. now the problem is that i want to integrate the

On Tue, 8 Sep 2020, Hugh Parsonage wrote: > Thanks Martin. On further testing, it seems that the segmentation > fault can only occur when the amount of obtainable memory is > sufficiently high. On my machine (admittedly with other processes > running): > > $ R --vanilla --max-mem-size=30G -e "x <- c(0L, -2e9:2e9)" > Segmentation fault > > $ R --vanilla

Dear List, I have tried a stratified Cox Regression, it is working fine, except for the "Anova"-Tests: Here the commands (should work out of the box): library(survival) d = colon[colon$etype==2, ] m = coxph(Surv(time, status) ~ strata(sex) + rx, data=d) summary(m) # Printout ok anova(m, test='Chisq') This is the output of the anova command: > Analysis of Deviance Table

>>>>> luke-tierney >>>>> on Tue, 8 Sep 2020 09:42:43 -0500 (CDT) writes: > On Tue, 8 Sep 2020, Martin Maechler wrote: >>>>>>> Martin Maechler >>>>>>> on Tue, 8 Sep 2020 10:40:24 +0200 writes: >> >>>>>>> Hugh Parsonage >>>>>>> on Tue, 8 Sep 2020

This is a follow-up to a query that was posted regarding some problems that emerge when running anova analyses for cox models, posted by Mathias Gondan: Matthias Gondan wrote: >* Dear List,*>**>* I have tried a stratified Cox Regression, it is working fine, except for*>* the "Anova"-Tests:*>**>* Here the commands (should work out of the box):*>**>*

I can only reproduce on Windows, but reliably (both 4.0.0 and 4.0.2): $> R --vanilla x <- c(0L, -2e9:2e9) # > Segmentation fault Tried to reproduce on Linux but the above worked as expected. Not an issue merely with the length of the vector; for example, x <- rep_len(1:10, 1e10) works, though the altrep vector must be long to reproduce: x <- c(0L, -1e9:1e9) #ok Segmentation

>>>>> Hugh Parsonage >>>>> on Tue, 8 Sep 2020 18:08:11 +1000 writes: > I can only reproduce on Windows, but reliably (both 4.0.0 and 4.0.2): > $> R --vanilla > x <- c(0L, -2e9:2e9) > # > Segmentation fault > Tried to reproduce on Linux but the above worked as expected. Not an > issue merely with the length of

Thanks Martin. On further testing, it seems that the segmentation fault can only occur when the amount of obtainable memory is sufficiently high. On my machine (admittedly with other processes running): $ R --vanilla --max-mem-size=30G -e "x <- c(0L, -2e9:2e9)" Segmentation fault $ R --vanilla --max-mem-size=29G -e "x <- c(0L, -2e9:2e9)" Error: cannot allocate vector

On Tue, 8 Sep 2020, Martin Maechler wrote: >>>>>> Martin Maechler >>>>>> on Tue, 8 Sep 2020 10:40:24 +0200 writes: > >>>>>> Hugh Parsonage >>>>>> on Tue, 8 Sep 2020 18:08:11 +1000 writes: > > >> I can only reproduce on Windows, but reliably (both 4.0.0 and 4.0.2): > > >> $> R

Unfortunately I only get [Thread 21752.0x4aa8 exited with code 3221225477] [Thread 21752.0x4514 exited with code 3221225477] [Thread 21752.0x3f10 exited with code 3221225477] [Inferior 1 (process 21752) exited with code 030000000005] (I'm guessing I would need to build an instrumented version of R, or can R be debugged using gdb with an off-the-shelf installation?) On Wed, 9 Sep 2020 at

On 9/8/20 4:48 PM, Hugh Parsonage wrote: > Unfortunately I only get > > [Thread 21752.0x4aa8 exited with code 3221225477] > [Thread 21752.0x4514 exited with code 3221225477] > [Thread 21752.0x3f10 exited with code 3221225477] > [Inferior 1 (process 21752) exited with code 030000000005] > > (I'm guessing I would need to build an instrumented version of R, or > can R

Dear addresses, I need perform a batch of 10 000 simulations for each of 4 options considered. (The idea is to obtain the parameter estimates in a heteroskedastic linear regression model - with additive or mixed heteroskedasticity - via the Kenward-Roger small-sample adjusted covariance matrix of disturbances). For this purpose I wrote an R program which would capture all possible options (true

Hello again, everytime I think I got something to work, the next issue comes up... I have the following data.frame, I want to visualize: > data_rb tld spam1 spam2 share 1 ca 826436 73452 0.0889 2 org 470550 25740 0.0547 3 de 156042 15531 0.0995 4 com 140753 7527 0.0535 5 edu 34845 2507 0.0719 6 net 12781 382 0.0299 7 ru 7648 18 0.0024