similar to: [Bug 953] New: Meta priority parsing is broken

https://bugzilla.netfilter.org/show_bug.cgi?id=1344 Bug ID: 1344 Summary: Segmentation fault in nft add rule ip ipv4table ipv4chain-1 tcp sport { 12345-54321 } Product: nftables Version: unspecified Hardware: All OS: Ubuntu Status: NEW Severity: critical Priority: P5

help Hello, I?m a statistic student in Austria and I have to do a survival analysis in R by using psplines as regressor. My problem is that I sometimes (I think it depends on the choose of the parameters) get a error message, but I do not know what it means. After that I tried the procedure with an example dataset R is providing. Although using the cancer dataset I also get this message. Input:

https://bugzilla.netfilter.org/show_bug.cgi?id=950 Summary: ct status Product: nftables Version: unspecified Platform: x86_64 OS/Version: All Status: NEW Severity: enhancement Priority: P5 Component: nft AssignedTo: pablo at netfilter.org ReportedBy: anarey at gmail.com Estimated Hours:

For some reason rake spec is totally crapping out on me. I don''t know what I did to make it break, the only thing I tried new was install haml, but even after removing it there is still a stack trace. Here is what I am getting- sparta at phalanx ff $ rake spec (in /Users/sparta/Projects/work/idastudios/ff)

(Sorry, I had the previous emails on a different machine.) Thanks to Prof Ripley for diagnosing the problem with inconsistent capitals under Win98. It's 'interesting': * I had ...\acepack\Src\Ace.f Avas.f and Rlsmo.f (tar'ed in a Unix machine and Ws_FTP'ed to the PC) * when the directory name was changed to ...\acepack\src it still didn't work *

I wrote: > Also I wrote: > > However, xl fails on config files which are missing the final > > newline. This should be fixed for 4.2. > > My patch for this didn''t make it into 4.2 RC4. Should this go into 4.2.0 or be held for 4.2.1 (or is it not 4.2.x material at all) ? Ian. From: Ian Jackson <ian.jackson@eu.citrix.com> Subject: [PATCH] libxl: Tolerate xl

predict.lm(..., type="terms") gives wrong standard errors. Below, I have provided what I believe are the necessary fixes. However, there are subtleties, and the code needs careful checking. Some of the looping is surely not necessary, but it is surely best to begin with the minimum necessary changes. My tests, including checks against S-PLUS, have extended to fitting spline curves. I

>From e980153 Tue Apr 25 14:42:27 2000 To: r-help@stat.math.ethz.ch Subject: Wrong SEs in predict.lm(..., type="terms") For what it is worth, I am using RW-1.0.0 under Windows 98. I submitted this earlier to r-help. There is one change below to my proposed corrected code: predict.lm(..., type="terms") gives wrong standard errors. Below, I have provided what I believe are

Dear R listers -- I have several questions about using the ppr command in the modreg module. I discovered -- quite by accident -- that if I re-order the data, I obtain different results. The output below shows what I mean. I have two datasets (dataset1 and dataset2) that are identical (tested using proc compare in SAS) except for the fact that the records are in different order. Below I have

Hi, I am a new user of R using R 2.8.1 in windows 2003. I have a csv file with single column which contain the 30,000 students names. There were typo errors while entering this student names. The actual list of names is < 1000. However we dont have that list for keyword search. I am interested in grouping/cluster these names as those which are similar letter to letter. Are there any

Full_Name: Yves Rosseel Version: 2.2.1 OS: i686-pc-linux-gnu Submission from: (NULL) (157.193.116.152) Dear developers, For the single-model case, the anova.mlm() function does not seem to handle multi-parameter predictors (eg factors) correctly. A toy example illustrates the problem: Y <- cbind(rnorm(100),rnorm(100),rnorm(100)) A <- factor(rep(c(1,2,3,4), each=25)) fit <- lm(Y ~ A)

Sorry about the lack of detail. I am running R v.1.2.2. I can recast my question (which I think I have partially answered) more succinctly as follows: 1. This seems to work (note that group takes values 1,2,3,4, or 5): my.newfun <- function(x) myfile <- lm(award ~ ilogemp + ilogage, x) test.by <- by(wintemp, as.factor(wintemp$group), my.newfun) 2. This does not work (leaving aside

Dear all, I have been doing tests using SVM, random forests and PPR. The data is from a data stream (that is, the data for training and for test is always increasing / changing). With SVM and random forests everything is ok, but with ppr there are situations where it crashes. For the examples I have used I noticed that if one of the variables has just one value (it can happen), it crashes for

Folks, The projection pursuit regression function in the base R seems to crash when the optimization level is set to zero, i.e. the initial ridge terms are accepted without refitting. I encountered this problem in an out-of-sample prediction exercise using predict. But further investigation suggests the issue is with the ppr fit and predict just sppeds up the crash. The other optlevels seem to be

I used the supersmoother function in the modreg package as follows: super <- supsmu(ilogemp,award) Then I decided that I might want additional explanatory variables (other than ilogemp) in my model. The ppr function in modreg seemed a logical extension of supsmu from univariate to multidimensional explanatory variables. As a "check" I ran the following: pprest <-

Dear R list: I want to make separate estimates for each level of the variable "group." After consulting many sources I am stumped as to why the following does not work: > wintemp <- subset(alltemp, winner==1) > my.ppr <- function(x) + { + if(nrow(x) >= 50) { + pprfile <- ppr(award~ilogemp, data=x,nterms=5,max.terms=10,optlevel=3) + summary(pprfile) +

Dear All, This is my first post, and probably (and hence apologies that) my question is very silly! I'm having issues with a the mvabund package (http://cran.r-project.org/web/packages/mvabund/index.html), and would be great to get some help! Here is the code (and files are attached): library(mvabund) ##visualizing data florabund <- read.csv("CPL_floristics_abund_v1d.csv",

Dear R users, I am trying to analyze multivariate abundance data using the mvabund package, but errors occur for several functions. I created a mvabund object named faunadat consisting of 8 dependent variables each containing 64 positive integer values (bact, fung, plant, omn, pred, orib, meso, spring). There are 4 factors: harv, rep, depth and lit. I then created a formula: >

Dear R listers -- The program below does the following tasks: 1. It creates a file (wintemp4) that is a subset of alldata4 consisting of "winner" records in 50 industry groups (about 5400 obs); 2. It defines a function (myppr1) that runs the ppr function in modreg once to generate goodness of fit (sum of squared errors) measures by number of terms included in model and then reruns

Hi, Recently, I installed the 1.1.0 version of R (for Windows), since it includes an implementation of Projection Pursuit (I failed to write my own version of PP as a standalone C++ program). As far as I know, R offers two interfaces/sintax for the ppr() function. The first one requieres a regression formula and a data frame. The other requieres X, a matrix with the explanatory variables, and Y,