similar to: grep

Could not get "which" to work, but my grep worked. Thanks. > which(grep("very|somewhat",names(goprobit.p$est))) Error in which(grep("very|somewhat", names(goprobit.p$est))) : argument to 'which' is not logical > grep("very|somewhat",names(goprobit.p$est)) [1] 6 7 8 9 10 11 12 13 28 29 30 31 32 33 34 35 50 51 52 53 54 55 56 57 On 7/12/2024

Yes. Any of the following worked. The pipe greater than (|>) is neat! Thanks. > v<-goprobit.p$est > names(v) |> grep("somewhat|very", x = _) ?[1]? 6? 7? 8? 9 10 11 12 13 28 29 30 31 32 33 34 35 50 51 52 53 54 55 56 57 > v |> names() |> grep("somewhat|very", x = _) ?[1]? 6? 7? 8? 9 10 11 12 13 28 29 30 31 32 33 34 35 50 51 52 53 54 55 56 57 >

Thanks. In this case below, what is "x"? I tried rownames(out) which did not work. Sorry. Does this sound like homework to you? On 7/12/2024 5:09 PM, Uwe Ligges wrote: > > > On 12.07.2024 10:54, Steven Yen wrote: >> Below is part a regression printout. How can I use "grep" to identify >> rows headed by variables (first column) with a certain label. In

Below is part a regression printout. How can I use "grep" to identify rows headed by variables (first column) with a certain label. In this case, I like to find variables containing "somewhath", "veryh",?"somewhatm", "verym", "somewhatc", "veryc","somewhatl", "veryl". The result should be an index 6:13 or

On 12.07.2024 10:54, Steven Yen wrote: > Below is part a regression printout. How can I use "grep" to identify > rows headed by variables (first column) with a certain label. In this > case, I like to find variables containing "somewhath", > "veryh",?"somewhatm", "verym", "somewhatc", "veryc","somewhatl",

?s 02:10 de 02/08/2024, Steven Yen escreveu: > Good Morning. Below I like statement like > > j<-grep(".r\\b",colnames(mydata),value=TRUE); j > > with the \\b option which I read long time ago which Ive found useful. > > Are there more or these options, other than ? grep? Thanks. > > dstat is just my own descriptive routine. > > > x > ?[1]

Good Morning. Below I like statement like j<-grep(".r\\b",colnames(mydata),value=TRUE); j with the \\b option which I read long time ago which Ive found useful. Are there more or these options, other than ? grep? Thanks. dstat is just my own descriptive routine. > x ?[1] "age"????????? "sleep"??????? "primary"????? "middle" ?[5]

which(grepl(....)) looks odd. Doesn't grep by itself return the correct vector of indices? Regards, Jorgen Harmse.? Message: 5 Date: Fri, 12 Jul 2024 17:42:05 +0800 From: Steven Yen <styen at ntu.edu.tw <mailto:styen at ntu.edu.tw>> To: Uwe Ligges <ligges at statistik.tu-dortmund.de <mailto:ligges at statistik.tu-dortmund.de>>, R-help Mailing List <r-help at

Hello, my question is about the data handling. I have a data set that is lined as: 4 1 17 1 1 -5.1536 -0.1668 -2.3412 -0.5062 0.9621 0.3640 0.3678 -0.5081 -0.2227 0.8142 -0.0389 -0.0445 -0.0578 -0.1175 -0.1232 0.8673 -0.1033 -0.0796 -0.0341 -0.1716 -0.1801 -0.7014 0.6578 0.5611 4 1 17 2 1 -5.1536 -0.1668 -2.3412 -0.5062 0.9621 0.3640 0.3678 -0.5081 -0.2227 0.8142 -0.0389 -0.0445

What is the easiest way to extract a value from a 'mer' object from glmer? The first I need is the trtpair Std.Dev. which in this case is 0.17542? I've managed to get the fixed effects numbers from summary(fednmaout)@coeffs but no luck with the Random effects stuff. TIA Jim > fednmaout Linear mixed model fit by REML Formula: lor ~ as.factor(t2) + as.factor(t3) + (1 |

Dear R-helpers, I have a linear model with a year effect (year is coded as a factor), i.e. the parameter estimates for each level of my year variable have significant P values (see some output below) and I am interested in testing: a) the overall effect of year; b) the significance of each year vis-a-vis every other year (the model output only tests each year against the baseline year). I'd

Dear Rlist, Using an example in box.cox.powers() help, I have the following warning message. example: library(car) >attach(Prestige) > box.cox.powers(income) Box-Cox Transformation to Normality Est.Power Std.Err. Wald(Power=0) Wald(Power=1) 0.1793 0.1108 1.6179 -7.4062 L.R. test, power = 0: 2.7103 df = 1 p = 0.0997 L.R. test, power = 1: 47.261 df = 1 p = 0

Dear R-helpers, I have a linear model with a year effect (year is coded as a factor), i.e. the parameter estimates for each level of my year variable have significant P values (see some output below) and I am interested in testing: a) the overall effect of year; b) the significance of each year vis-a-vis every other year (the model output only tests each year against the baseline year). I'd

Hello, I have been attempting to set up a lme and have looked at numerous posts including 'R's lmer cheat-sheet' as well as reading a number of papers and other resources including R help, but I am still a little confused on how to write my model (I thought I had it). I have asked a number of questions on different forums; most of which have been resolved. My main concern right now

On Jul 24, 2011, at 3:02 AM, Duncan Sands wrote: > A big compile time regression. Any ideas? > > Ciao, Duncan. False alarm. For some reason that I have not yet been able to figure out, these tests run significantly more slowly when I run them during the daytime, which I did for that run. I checked a few of the worst regressions reported here and they all recovered in subsequent

A big compile time regression. Any ideas? Ciao, Duncan. On 22/07/11 19:13, llvm-testresults at cs.uiuc.edu wrote: > > bwilson__llvm-gcc_PROD__i386 nightly tester results > > URL http://llvm.org/perf/db_default/simple/nts/253/ > Nickname bwilson__llvm-gcc_PROD__i386:4 > Name curlew.apple.com > > Run ID Order Start Time End Time > Current 253 0 2011-07-22 16:22:04

Hi Elaine I do not use it very often. I programmed it to mimic Minitab functions (partly) with some adons from czech statistics textbook written by M.Meloun (meloun militky statistics - first hit in google) Basically you can have your data in some data frame or they can be as separated vectors. The function itself expects input of 3 vectors, but you can easily to modify it for imput as

Hello all, I am trying to understand how to specify nested factors when using coxph(), and if it is appropriate to nest these factors in my situation. In the simplest form, I am testing two different temperatures, with each temperature being performed twice in different experimental periods (e.g. Temp5 performed in Period A and C, Temp4 performed in Period B and D) I am trying to see if survival

hello: my data looks like: time1  time2   event  catagoria 2004    2006        1            C 2004    2005        0            C 2005    2010        1            E 2007    2009        1            C 2006    2007        0            E 2008    2010        0            C 2008    2010        1            E ... and the census interval is 1 year I have tried  this

On Fri, Sep 14, 2007 at 11:42:18PM -0700, Tanya Lattner wrote: > The 2.1 pre-release (version 1) is available for testing: > http://llvm.org/prereleases/2.1/version1/ > > [...] > > 2) Download llvm-2.1, llvm-test-2.1, and the llvm-gcc4.0 source. > Compile everything. Run "make check" and the full llvm-test suite > (make TEST=nightly report). > > Send