similar to: Help on not matching object lengths

Hi R Fans, I stumbled across a strange (I think) bug in R 2.9.1. I have read in a data file with 5934 rows and 9 columns with the commands: daten = data.frame(read.table("C:/fussball.dat",header=TRUE)) Then I needed a subset of the data file: newd = daten[daten[,1]!=daten[,2],] --> two values do not meet the logical specification and are dropped. The strange thing about it:

 Hi:  Using nls how can I increase the numbers of iterations to go beyond 50.  I just want to be able to predict for the last two weeks of the year.  This is what I have:  weight_random <- runif(50,1,24)  weight <- sort(weight_random);weight weightData <- data.frame(weight,week=1:50)                          weightData plot(weight ~ week, weightData) M_model <- nls(weight ~ alpha +

?s 17:38 de 30/11/2023, Robert Baer escreveu: > I am having trouble using back ticks with the R extractor function > 'predict' and an lm() model.? I'm trying too construct some nice vectors > that can be used for plotting the two types of regression intervals.? I > think it works with normal column heading names but it fails when I have > "special"

Hi list, This looks similar to the problem reported here https://stat.ethz.ch/pipermail/r-devel/2006-April/037199.html by Henrik Bengtsson a long time ago. It is very sporadic and non-reproducible. Henrik, do you remember if your code was using reg.finalizer()? I tend to suspect it but I'm not sure. I've been hunting this bug for months but today, and we the help of other Bioconductor

Hi, I'm using a loop to evaluate several models by taking adjacent variables from my dataframe. When i try to get predictions for new values, i get an error message about a missing variable in my new dataframe. Below is an example adapted from ?gam in mgcv package library(mgcv) set.seed(0) n<-400 sig<-2 x0 <- runif(n, 0, 1) x1 <- runif(n, 0, 1) x2 <- runif(n, 0, 1) x3 <-

All, I'm seeing duplication of DICompileUnits in a pass that worked in 3.8. I assume I'm doing something wrong. Would someone be willing to point me in the right direction? The below minimized pass reproduces my issue in 4.0 with the following error: DICompileUnit not listed in llvm.dbg.cu !1707 = distinct !DICompileUnit(language: DW_LANG_C_plus_plus, file: !1, producer: "clang

Dear R experts Sorry for this question M1 <- 1:10 lcd1 <- c(11, 22, 33, 44, 11, 22, 33, 33, 22, 11) lcd2 <- c(22, 11, 44, 11, 33, 11, 22, 22, 11, 22) lcd3 <- c(12, 12, 34, 14, 13, 12, 23, 23, 12, 12) #generating variables through sampling pvec <- c("PR1", "PR2", "PR3", "PR4", "PR5", "PR6", "PR7",

Thank you. What I need to do to address this? Open an issue on bugs.llvm.org? I'm not sure what the fix needs to be in the cloner. On Thu, Jun 8, 2017 at 4:19 PM, Peter Collingbourne <peter at pcc.me.uk> wrote: > There have in the past been bugs in the cloner involving duplicate > DICompileUnits (see e.g. https://reviews.llvm.org/D29240), this one may > need a similar fix.

Hi everyone, My apologies if this isn?t the right place to submit this?I?m new to the R-devel community and still figuring out what is where. If people want to skip my writeup and just look at the code, I?ve made a repository for it here: https://github.com/ahl27/new_dendrapply/tree/master. I?m not quite sure how to integrate it into a fork of R-devel; the package structure is different from

Good day everyone, Can anyone suggest an effective method to solve the following problem: I have 2 dataframes D1 and D2 as follows: D1: dates ws wc pwc 2005-10-19:12:00 10.8 80 81 2005-10-20:12:00 12.3 5 15 2005-10-21:15:00 12.3 3 15 2005-10-22:15:00 11.3 13 95 2005-10-23:12:00 12.3 13 2 2005-10-24:15:00 10.3 2 95 2005-10-25:15:00 10.3 2 2 D2:

Hi Maria If you have problems just start with a small model with predictions and then plot with xyplot the same applies to xyplot Try library(gamm4) spring <- dget(file = "G:/1/example.txt") str(spring) 'data.frame': 11744 obs. of 11 variables: $ WATERBODY_ID : Factor w/ 1994 levels "GB102021072830",..: 1 1 2 2 2 3 3 3 4 4 ... $ SITE_ID

Dear all, I'm a fairly new R user having two questions regarding gam: 1. The prediction example on p. 38 in the mgcv manual. In order to get predictions based on the original data set, by leaving out the 'newdata' argument ("newd" in the example), I get an error message "Warning message: the condition has length > 1 and only the first element will be used in: if

Full_Name: John Gavin Version: 2.1.0 patched 18-04-05 OS: windows XP SP2 Submission from: (NULL) (139.149.1.203) Hi, I suspect that there may be a bug in utils::setRepositories(). Starting with > getOption("repos") CRAN CRANextra "@CRAN@"

I am working on Johansen cointegration test, using urca and var package. in the selection of var, I have got following results. >VARselect(newd, lag.max = 10,type = "none") $selection AIC(n) HQ(n) SC(n) FPE(n) 6 6 6 5 $criteria 1 2 3 4 5 6 7 8 9 AIC(n) -3.818646e+01 -3.864064e+01

Hey List, I did a multiple regression and my final model looks as follows: model9<-lm(calP ~ nsP + I(st^2) + distPr + I(distPr^2)) Now I tried to predict the values for calP from this model using the following function: xv<-seq(0,89,by=1) yv<-predict(model9,list(distPr=xv,st=xv,nsP=xv)) The predicted values are however strange. Now I do not know weather just the model does not fit

I am having trouble using back ticks with the R extractor function 'predict' and an lm() model.? I'm trying too construct some nice vectors that can be used for plotting the two types of regression intervals.? I think it works with normal column heading names but it fails when I have "special" back-tick names.? Can anyone help with how I would reference these?? Short of

thank you for your valuable reply. I have attached my commands, results, and data with this mail..maybe it will be beneficial for you to feedback. On Tue, Nov 21, 2017 at 9:13 PM, Jeff Newmiller <jdnewmil at dcn.davis.ca.us> wrote: > Your example is incomplete... as the bottom of this and every post says, > we need to be able to proceed from an empty R environment to wherever you

Your example is incomplete... as the bottom of this and every post says, we need to be able to proceed from an empty R environment to wherever you are having the problem (reproducible), in as few steps as possible (minimal). The example needs to include data, preferably in R syntax as the dput function creates... see the howtos referenced below for help with that. [1], [2], [3] You also need to

Dear all,? I hope that you can help me on this. I have been struggling to figure this out but I haven't found any solution. I am running a generalised mixed effect model, gamm4, for an ecology project. Below is the code for the model: model<-gamm4(LIFE.OE_spring~s(Q95, by=super.end.group)+Year+Hms_Rsctned+Hms_Poaching+X.broadleaved_woodland? ? ? ? ? ? ?+X.urban.suburban+X.CapWks,

Here's my little discussion example for a quadratic regression: http://pj.freefaculty.org/R/WorkingExamples/regression-quadratic-1.R Students press me to know the benefits of poly() over the more obvious regression formulas. I think I understand the theory on why poly() should be more numerically stable, but I'm having trouble writing down an example that proves the benefit of this. I