similar to: EVER_1.1

Thanks for the report, I can reproduce. In Rgui, the output of "print(cars)" is incorrect, the line numbers appear as part of the command prompt string (printed in reverse order, without newlines), while the rest of the output is correctly displayed. This is a bug, I will have a closer look Best, Tomas On 06/11/2018 11:10 AM, Diego Zardetto wrote: > Dear all, > > >

Dear all, I would like to have your opinion about an issue I have recently run into while using tcltk in R 3.5.0 under Windows 7 64bit. Here is a reproducible example of the issue, along with information about platform and OS. ############################################################### # R 3.5.0 issue: print does not work properly for data.frames # # when called

Hi R-experts, I want to use the jackknife function from the bootstrap package onto a linear model. I can't figure out how to do that. The manual says the following: # To jackknife functions of more complex data structures, # write theta so that its argument x # is the set of observation numbers # and simply pass as data to jackknife the vector 1,2,..n. # For example, to jackknife #

Is there a way to create a BRR svrepdesign from a survey design when the number of PSUs is odd in one or more stratum? Creating a JKn svrepdesign with that condition works okay, but when I tried to create a svrepdesign with type="BRR" I get an error and this message: "Can't split with odd numbers of PSUs in a stratum" I get that message when I tell it to merge the

Hi dear all, Can aynone help me about delete-d jackknife usually normal jackknife code for my data is: n <- nrow(data) y <- data$y z <- data$z theta.hat <- mean(y) / mean(z) print (theta.hat) theta.jack <- numeric(n) for (i in 1:n) theta.jack[i] <- mean(y[-i]) / mean(z[-i]) bias <- (n - 1) * (mean(theta.jack) - theta.hat) print(bias) but how i can apply delete-d jackknife

Below is a SIMEX object that was generated with the "simex" function from the "simex" package applied to a logistic regression fit. From this mountain of information I would like to extract all of the values summarized in this line: .. ..$ variance.jackknife: num [1:5, 1:4] 1.684 1.144 0.85 0.624 0.519 ... Can someone suggest how to go about doing this? I can extract the

While doing pls I found the following problem > BHPLS1 <- plsr(GroupingList ~ PCIList, ncomp = 10, data = PLSdata, jackknife = >FALSE, validation = "LOO") when not enabling jackknife the command works fine, but when trying to enable jackknife i get the following error. >BHPLS1 <- plsr(GroupingList ~ PCIList, ncomp = 10, data = PLSdata, jackknife = >TRUE,

Dear all I have used the lda and predict functions to classify a set of objects of unknown origin. I would like to use a jackknife reclassification to assess the degree to which the outcomes deviate from that expected by chance. However, I can't find any function that allows me to do this. Any suggestions of how to generate the jackknife reclassification to assess classification accuracy?

Hi dear all, Can someone help me about detection of outliers using jackknife after bootstrap algorithm? -- View this message in context: http://r.789695.n4.nabble.com/jackknife-after-bootstrap-tp3041634p3041634.html Sent from the R help mailing list archive at Nabble.com. [[alternative HTML version deleted]]

Is there a routine in the boot package to get the jackknife-after- bootstrap influence values? That is, the influence values of a jackknife of the bootstrap estimates? I can see how one would go about it from the jack.after.boot code, but that routine only makes pretty pictures. It wouldn't be hard to write, but I find it hard to believe this isn't part of the package already. Thanks

Hi All, I'm not able to figure out how to perform a Jackknife test for a 2-sample dispersion test in R. Is there a built-in function to perform this or do we have to take a step by step approach to calculate the test statistic? Any help would be awesome. Thanks! -- View this message in context: http://r.789695.n4.nabble.com/Jackknife-for-a-2-sample-dispersion-test-tp4444274p4444274.html

Hi, I have the following jackknife code which is much slower than my colleagues C code. Yet I like R very much and wonder how R experts would optimize this. I think that the for (i in 1:N_B) part is bad because Rprof() said sum() is called very often but I have no idea how to optimize it. #O <- read.table("foo.dat")$V1 O <- runif(100000); k=100 # size of block to delete

Hello, and welcome to the NUT community! :) On one hand, it would generally help to read up the documentation about NUT architecture, seeing as it is a crucial part of your systems' uptime and data integrity. On another hand, for this particular use-case: it is quite possible to set up monitoring-only systems which only inform you if some *other* NUT data server has had interesting

Can you better this String acronym method? def acronym name letters=[] name.each_char {|char| letters<<char if char[0]>=65 and char[0]<=90} acronym = letters.join " " end chris -- Posted via http://www.ruby-forum.com/.

On Dec 21, 2011, at 7:05 PM, 陳韋任 wrote: >> "LLVM" is officially no longer an acronym. The acronym it once expanded too was confusing, and inappropriate almost from day 1. :) As LLVM has grown to encompass other subprojects, it became even less useful and meaningless. >> >> In short, it is just "The LLVM Project", and LLVM doesn't stand for anything

> "LLVM" is officially no longer an acronym. The acronym it once expanded too was confusing, and inappropriate almost from day 1. :) As LLVM has grown to encompass other subprojects, it became even less useful and meaningless. > > In short, it is just "The LLVM Project", and LLVM doesn't stand for anything anymore. It is a nice short domain name though :)

Hello, Is there a way to get complex sample variances in the survey package on summary statistics other than means? If not, can they be added to a future version? It would be be great to have them on totals, quantiles, ratios, and tables (eg row percent, columns percent, etc). Thanks. Fred --------------------------------- [[alternative HTML version deleted]]

The R-exts manual still says Note also that for running @LaTeX{}, the Debian @acronym{GNU}/Linux @acronym{CRAN} check systems use the Debian TeXLive at footnote{currently the long obsolete TeXLive 2009.} distribution (@uref{http://packages.debian.org/@/en/@/sid/@/texlive}); the Fedora and and what is in the footnote has not been true for quite some time as a visit to the URL (or to the

Folks, Thanks for the help with the hier.part analysis. All the problems stemmed from an import problem which was solved with file.chose(). Now that I have the variables that I'd like to use I need to run some GLM models. I think I have that part under control but I'd like to use a jackknife approach to model validation (I was using a hold out sample but this seems to have fallen out

The LLVM term in Wikipedia still uses the old explanation. http://en.wikipedia.org/wiki/Low_Level_Virtual_Machine On Wed, Dec 21, 2011 at 11:15 PM, Chris Lattner <clattner at apple.com> wrote: > > On Dec 21, 2011, at 7:05 PM, 陳韋任 wrote: > >>> "LLVM" is officially no longer an acronym.  The acronym it once expanded too was confusing, and inappropriate almost