search for: 4.38

I've a matrix like this: 1985 1.38 1.27 1.84 2.10 0.59 3.47 1986 1.05 1.13 1.21 1.54 0.21 2.14 1987 1.33 1.21 1.77 1.44 0.27 2.85 1988 1.86 1.06 2.33 2.14 0.55 1.40 1989 2.10 0.65 2.74 2.43 1.19 1.45 1990 1.55 0.00 1.59 1.94 0.99 2.14 1991 0.92

dear R-users, I am facing a quite regular and basic problem when it comes to dealing with datasets, but I cannot find any satisfying answer so far. I have a messy dataset of galaxies like that : And XVIII 000214.5+450520 0.69 17 9 0.00 -8.7 26.8 6.44 6.78 < 6.65 -44 0.5 MESSIER031 0.6 1.54 PAndAS-03 000356.4+405319 0.10 17 0.00 -3.6 27.8 4.38

Hello. I am trying to do a non-linear fit using the 'nls' command. The data that I'm using is as follows pH k 1 3.79 34.21 2 4.14 25.85 3 4.38 20.45 4 4.57 15.61 5 4.74 12.42 6 4.92 9.64 7 5.11 7.30 8 5.35 5.15 9 5.67 3.24 with a transformation of pH to H <- 10^-pH When using the nls command for a set of parameters - a, b and c, I receive two sets of errors: >

Hello everyone I appologize for my lack of experience in statistical methods. I am an R user begginer and I am running a logit model using "zelig" and "pcse" packages. I will go to the point and is that Im having problems with interpreting the results of my models.. It is really simple (I guess for the most advanced scholars) however I really dont understand how to interpret

Dear R users, I'm trying figuring out with forest plot and rmeta. Here's my code... library(rmeta) tabletext <- structure(c("", NA, "Sex", "[F]", "[M]", NA, "Age class", "(0,60]", "(60,80]", NA, "Karnofsky class", "[70;90]",

Duncan, With the commit from http://lists.cs.uiuc.edu/pipermail/llvm-commits/Week-of-Mon-20121203/158488.html, the Polyhedron 2005 benchmarks complete again on x86_64-apple-darwin12. The result are similar to what were seen with FSF gcc 4.6.2svn and llvm/dragonegg 3.0 (which was the last release that passed pb05) http://lists.cs.uiuc.edu/pipermail/llvmdev/2011-October/044091.html. Jack

It looks like fixed width. I just used the last position of each field to get the size and used the 'readr' package; > input <- "And XVIII 000214.5+450520 0.69 17 9 0.00 -8.7 26.8 6.44 6.78 < 6.65 -44 0.5 MESSIER031 0.6 1.54 + PAndAS-03 000356.4+405319 0.10 17 0.00 -3.6 27.8 4.38 2.8 MESSIER031

I am just assuming this can be done, but I have not gotten close to making it happen. I have a data file with about 1 million rows with 1470 unique subjects. Each row represents a small set of observations made on a specific date for a single subject. I would like to transform the data so that I have an R object with a single entry for each subject and start date and vectors for the

Hello I would like to transfer some Splus functions in R. But I have a problem first about this assignation in Splus : xnom <- deparse(substitute(x)) I am a bad programmer : I don't understand the R help How to modify these functions ? Thank you very much for your help Here are the four functions and a data test

Hi Jack, thanks for these numbers. > With the commit from http://lists.cs.uiuc.edu/pipermail/llvm-commits/Week-of-Mon-20121203/158488.html, > the Polyhedron 2005 benchmarks complete again on x86_64-apple-darwin12. The result are similar to what > were seen with FSF gcc 4.6.2svn and llvm/dragonegg 3.0 (which was the last release that passed pb05) >

Hi, I need further help with my GAMs. Most models I test are very obviously non-linear. Yet, to be on the safe side, I report the significance of the smooth (default output of mgcv's summary.gam) and confirm it deviates significantly from linearity. I do the latter by fitting a second model where the same predictor is entered without the s(), and then use anova.gam to compare the

Is this a fixed width format? If so, read.fwf() in base, or read_fwf() in the readr package will solve the problem. You may need to trim trailing spaces though. B. > On Oct 5, 2017, at 10:12 AM, jean-philippe <jeanphilippe.fontaine at gssi.infn.it> wrote: > > dear R-users, > > > I am facing a quite regular and basic problem when it comes to dealing with datasets,

Dear list member, My question is related to input file format to an Anova from car package. Here is an example of what I did: My file format is like this (and I dislike the idea that I will need to recode it): Hormone day Block Treatment Plant Diameter High N.Leaves SH 23 1 1 1 3.19 25.3 2 SH 23 1 1 2 3.42 5.5 1 SH 23 1 2 1 2.19 5.2 2 SH 23 1 2 2 2.17 7.6 2 CH 23 1 1 1 3.64 6.5 2 CH 23 1 1 2

I'd like to superimpose a ksmooth() onto a barplot(). My data is: > d 2009-06-20 2009-06-21 2009-06-22 2009-06-23 2009-06-24 2009-06-25 2009-06-26 2009-06-27 2009-06-28 2009-06-29 2009-06-30 2009-07-01 2009-07-02 Same Breed (B) 12.64 21.08 13.52 12.51 13.71 9.91 14.24 7.18 11.81 5.92 12.04 17.96

Hi, I noticed some time ago that, for instance, named vectors that are really makes str() really slow when displaying the names attribute. I don't know exactly when this started, but it wasn't the case say 1-2 years ago. Example (on a WinXP 1.8GHz): > s <- 1:1000; names(s) <- s > system.time(str(s)) Named int [1:1000] 1 2 3 4 5 6 7 8 9 10 ... - attr(*, "names")=

Hi All I have been struggling with this model for some time now and I just can't get it to work correctly. The messages I get when running the code is: DLSODA- Warning..Internal T (=R1) and H (=R2) are such that in the machine, T + H = T on the next step (H = step size). Solver will continue anyway. In above message, R = [1] 0 0 DINTDY- T (=R1) illegal In above message, R = [1]

Summary ======= I'm planning on adjusting SimplifyCFG so that it doesn't turn two-entry phi nodes into selects until later in the pass pipeline, to give passes which can understand phis but not selects more opportunity to optimize. The thing I'm trying to do which made me think of doing this is described below, but from the benchmarking I've done it looks like this is overall a

Dear all, I am trying to use the crr function in the cmprsk package version 2.2 to analyse 198 observations.I have receive the error in solve.default. Can anyone give me some insights into where the problem is? Thanks here is my script : cov=cbind(x1,x2) z<-crr(ftime,fstatus,cov)) and data file: x1 x2 fstatus ftime 0 .02 1 263 0 .03 1 113 0 .03 1 523

I tried toy problems and there doesn't seem to be a basic problem between lm() and ts objects: X = data.frame(x=c(1,2,7,9), y=c(7,2,3,1)) lm(y ~ x, X) X <- lapply(X, function(x) ts(x, frequency=12, start=c(1994,7))) lm(y ~ x, X) and this works fine - whether you do an lm() before or after making ts objects, it's okay. But I have a situation where things aren't okay.

Hi all! I'm new to this forum so please excuse me if I don't conform perfectly to the protocols on this board! I'm trying to get an estimate of true prevalence based upon results from an imperfect test. I have various estimates of se/sp which could inform my priors (at least upper and lower limits even if with a uniform distribution) and found the following code on this website..