similar to: ls -lrt reversal

configure uses clock_gettime to check whether -lrt is needed - and don''t check other functions. With glibc 2.17 clock_gettime is part of libc, so use timer_gettime instead, which is in -lrt in old and new versions of glibc. Signed-off-by: Olaf Hering <olaf@aepfle.de> --- configure | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/configure b/configure index

Dear List, having searched the help and archives, I have the impression that there is no automatic model selection procedure implemented in R that includes/excludes predictors in logistic regression models based on LRT P-values. Is that true, or is someone aware of an appropriate function somewhere in a custom package? Even if automatic model selection and LRT might not be the most appropriate

Hi there, This is not a strictly related R question; I apologize for this. I'm interest in simulate the sampling distribution of the LRT, testing for trend among the levels of some categorical variable X in a regression model. (in practice this is achieved by assigning scores to the levels of X and fitting such numeric variable). To simulate the sampling distribution the steps are: 1.

On Wed, May 1, 2013 at 09:21:17AM -0700, Matt Wilson wrote: > On Mon, Apr 29, 2013 at 03:40:13PM +0200, Olaf Hering wrote: > > Ping > > Makes sense. > > Acked-by: Matt Wilson <msw@amazon.com> > > > On Wed, Jan 16, Olaf Hering wrote: > > > > > Ping > > > > > > On Wed, Dec 05, Olaf Hering wrote: > > > > > > >

On my setup with glibc-2.8, benchmark_residual linkage fails with undefines references to clock_gettime(). Adding -lrt fixes that. The following is a small patch for it. Regards. -- O.S. diff --git a/configure.ac b/configure.ac index 993ac33..392485e 100644 --- a/configure.ac +++ b/configure.ac @@ -437,6 +437,11 @@ if test x$enable_stack_smash_protection = "xyes" ; then

Hello !! I'm recently having a debate with my PhD supervisor regarding how to write the result of a likelihood ratio test in an article I'm about to submit. I analysed my data using "lme" mixed modelling. To get some p-values for my fixed effect I used model simplification and the typical output R gives looks like this: model2 = update ( model1,~.-factor A) anova (model1,

HI, Suppose I have the following data structure. LRT tp 1 1.50654010 522 2 0.51793929 522 3 0.90340299 522 4 1.20293325 522 5 1.05578774 523 6 0.01617942 523 7 0.68183543 523 8 0.43820244 523 9 1.14123995 524 10 0.05809550 524 11 0.93061597 524 12 1.39739700 524 13 1.05220953 525 14 0.03471461 525 15 0.63168798 525 16 1.40592603 525 17 1.41884492 526 18

I would like to try a likelihood ratio test in place of waldtest. Ideally I'd like to provide two glm models, the second a submodel of the first, in the style of lrt (http://www.pik-potsdam.de/~hrust/tools/farismahelp/lrt.html). [lrt takes farimsa objects] Does anyone know of such a likelihood ratio test? Chris Elsaesser, PhD Principal Scientist, Machine Learning SPADAC Inc. 7921

On my Centos box with: uname -r 2.6.18-164.6.1.el5 I tried to mount my 2T external drive with: mount -t ntfs /dev/sdg1 /mnt/wd and I get: mount: unknown filesystem type 'ntfs' Thanks in advance for your help. Mike.

# HG changeset patch # User Ian Campbell <ian.campbell@citrix.com> # Date 1300271932 0 # Node ID 7e326d27d899a3133479c8b7c983f660cdeda48c # Parent f35234b6636a0410a7d5eaa409e98ebe59080e4f tools: do not link against unused libraries. A fair few things under tools link against libraries which they don''t even use. Most of this appears to come from copy-and-pasting previous Makefile

Dovecot version: 2.2.15 Tinycdb: 0.78 I'm attempting to compile dovecot --with-cdb, but keep getting into a problem with cdb: ======================== libtool: link: gcc -std=gnu99 -g -O2 -Wall -W -Wmissing-prototypes -Wmissing-declarations -Wpointer-arith -Wchar-subscripts -Wformat=2 -Wbad-function-cast -fno-builtin-strftime -Wstrict-aliasing=2 -Wl,--as-needed -o .libs/anvil main.o

Jerry Kemp <dovecot at oryx.us> wrote: > same ENV variable setup and configure statement as originally used, but again, :( > ended up failing here: > .......................................................................... > libtool: link: gcc -std=gnu99 -g -O2 -Wall -W -Wmissing-prototypes > -Wmissing-declarations -Wpointer-arith -Wchar-subscripts -Wformat=2 >

Hello, I am using the following model model1=lmer(PairFrequency~MatingPair+(1|DrugPair)+(1|DrugPair:MatingPair), data=MateChoice, REML=F) 1. After reading around through the R help, I have learned that the above code is the right way to analyze a mixed model with the MatingPair as the fixed effect, DrugPair as the random effect and the interaction between these two as the random effect as well.

Hi, I'm interested in building a Cox PH model for survival modeling, using 2 covariates (x1 and x2). x1 represents a 'baseline' covariate, whereas x2 represents a 'new' covariate, and my goal is to figure out where x2 adds significant predictive information over x1. Ideally, I could get a p-value for doing this. Originally, I thought of doing some kind of likelihood ratio

Dear all, I noticed the following while playing around with fitting log-linear models to contingency tables using R 1.8.1, but the problem also exists under R 1.9.0. A reproducible example uses the following contingency table: > library(MASS) > data(quine) > tmp <- with(quine, expand.grid(Eth=levels(Eth), Sex=levels(Sex), + Lrn=levels(Lrn), Age=levels(Age)))

On Tue, Mar 10, 2015 at 2:22 AM, Jeffrey 'jf' Lim <jfs.world at gmail.com> wrote: > On Tue, Mar 10, 2015 at 2:15 AM, Jeffrey 'jf' Lim <jfs.world at gmail.com> > wrote: > >> Dovecot version: 2.2.15 >> Tinycdb: 0.78 >> >> I'm attempting to compile dovecot --with-cdb, but keep getting into a >> problem with cdb: >>

Dear expeRts, there is obviously a general trend to use model comparisons, LRT and AIC instead of Wald-test-based significance, at least in the R community. I personally like this approach. And, when using LME's, it seems to be the preferred way (concluded from postings of Brian Ripley and Douglas Bates' article in R-News 5(2005)1), esp. because of problems with the d.f. approximation.

I've been looking over system utility functions that we might want to add to R. A few come out of specific needs, others from looking at other systems and what people are using system() for. I've taken account of Paul Gilbert's comments posted here a while ago (and I think covered all except the use of mailers). We currently have date *.socket file.create file.exists file.remove

Hi, What is the difference between the R installation from source and the R installation from ubuntu repositories. Specifically when I install R-3.1.1 on ubuntu 14.04 from sources ldflags and CXXFLAGS are different that those from the installation from a repo. Installation from sources: R CMD config --ldflags -Wl,--export-dynamic -fopenmp -L/home/prana/prana_R/third-party/install/lib/R/lib

I got latest (13601) yesterday evening. This doesn''t seem to work to do Restore (at least of the Windows test-image that I''ve been using for testing previously). The VM restores reasonably OK, but it jumps to an invalid address shortly after restoring, giving a D1 blue-screen error (DRIVER_IRQL_LESS_OR_EQUAL), which turns out to be "page-fault in driver" after I