similar to: Adjusted patches for xen-unstable and current xen tip

Processing commands for control at bugs.debian.org: > reassign 463121 xen-unstable Bug#463121: xen-unstable non non-pae hypervisor package is not pae Bug reassigned from package `xen-unstable' to `xen-unstable'. > -- Stopping processing here. Please contact me if you need assistance. Debian bug tracking system administrator (administrator, Debian Bugs database)

Hello, I hope that this is an appropriate for this list - please educate me if not. Having cloned the unstable repository and attempted to run "make mkpatches" I found that it failed because it couldn''t download linux.2.6.16-rc4.tar.bz2 from kernel.org. This is because it''s looking for it in /pub/linux/kernel/v2.6 when in fact it is to be found in

Hi Ian, after our conversation on IRC in #debian-xen today, I updated the packaging to the latest 4.10-stable commit (since there's no 4.10.1 release yet) and smoke-tested the package on a testing/unstable dom0 running a PVHv2 guest. Can you please review and sponsor the upload of a first Xen 4.10 package to Debian unstable? The work which has been done to arrive at this point from the

Dear all, Apologies if this question is bit theoretical and for the longish email. I am meta-analyzing the coefficients and standard errors from multiple studies where the raw data is not available. Each study analyst runs a model that includes an interaction term for, say, between sex and smoking and age. Here is an illustrative example example for one study: set.seed(1066) status

I've resolved the conflicts between the xen-unstable svn tree's patchset and xen-unstable 16319 (which was the tip a few days ago). The result is below, as the output of `svn diff' - so a series of interdiffs, unfortunately. Also, I noticed that after installing the resulting packages, it wasn't able to correctly select the xen-unstable tools; instead, it fell back to the default.

Hello, I want to fit a GEE with a user-defined link function. For the user-defined link-function I still read http://finzi.psych.upenn.edu/R/Rhelp01/archive/6555.html and http://finzi.psych.upenn.edu/R/Rhelp02a/archive/25727.html. Only for testing purposes I added a new link function (corlogit) in make.link (as well as in binomial) with exactly the same code as logit before using my code.

Hi, I would like to see if a matching variable is an effect-modifier in a conditional logistic regression. Naturally, the matching variable can't enter directly in the model but as an interaction with terms that are in. However, I have problems in formulating the correct model the term that's already in the model is a factor. I am using treatment contrasts and the problem is that if I

Hi I am a new R user and I did try elrm package to do Exact Logistic regression for my dataset ( about 170 patients with a binary dependent variable against age and 6 other binary covariates), I did not have n column because it was about individuals, I made n column with 1 for each individual, here is my code and result: > > #### Libraries needed #### > >

Bother! This cold has made me accident-prone. I meant to hit Reply-all. Clarification below. -------- Original Message -------- Subject: Re: [R] Parameterization puzzle Date: Fri, 21 Jul 2006 19:10:03 +1200 From: Murray Jorgensen <maj at waikato.ac.nz> To: Prof Brian Ripley <ripley at stats.ox.ac.uk> References: <44C063E5.3020703 at waikato.ac.nz>

Hello, I have compared the potentials of R and Stata about GLMM, analysing the dataset 'ohio' in the package 'faraway' (the same dataset is analysed with GEE in the book 'Extending the linear model with R' by Julian Faraway). Basically, I've tried the 2 commands 'glmmPQL' and 'glmer' of R and the command 'xtmelogit' of Stata. If I'm not

Hi, I am trying to fit a ordinal GEE model using ordgee {geepack}. In order to check the validity of the function, I specified the correlation structure as independence (i.e. constr = "independence") and compared the result with that using polr {MASS}. Because a GEE model with an independent working correlation structure is equivalent to an ordinary GLM model, we would expect the same

I recently posted a question concerning an inconsistency of expand.grid in defining the reference level of the factors. > > expand.grid(x = c("b", "a"), y = c(1, 2))$x > [1] b a b a > Levels: b a # reference level is b > > expand.grid(x = c("b", "a"))$x > [1] b a > Levels: a b # reference level is a Thank you

On Mon, Sep 21, 2015 at 9:18 AM, Pasi K?rkk?inen <pasik at iki.fi> wrote: > On Mon, Sep 21, 2015 at 11:10:06AM +0300, Pasi K?rkk?inen wrote: >> Hi, >> >> On Wed, Sep 09, 2015 at 02:24:15PM +0100, George Dunlap wrote: >> > Updated Xen 4.4.3 packages have passed my local smoke tests, and are >> > now available. >> > >> > Full C7 release

Consider the following example (based on an example in Pat Altham's GLM notes) pyears <- scan() 18793 52407 10673 43248 5710 28612 2585 12663 1462 5317 deaths <- scan() 2 32 12 104 28 206 28 186 31 102 Smoke <- gl(2,1,10,labels=c("No","Yes")) Age <- gl(5,2,10,labels=c("35-44","45-54","55-64","65-74","75-84"),

Hello there, I have two groups (men and women) and I know per group how many of them smoke or don't smoke (women 40 of 200; men 100 of 300). I would like to know how I can compare in R if men and women differ significantly in their smoking. However, because there are more men in the sample than women I cannot just compare the number of smokers and non-smokers in both groups, right?! (I would

Hi useRs, Many studies of the link between red meat and colorectal cancer use Cox proportional hazards with (among other things) a gender covariate. If it is true that men eat more red meat, drink more alcohol and smoke more than women, and if it is also true that alcohol and tobacco are known risk factors then why does it make sense to "adjust" for gender? I would think that in this

I see a ton of past archive mails for pam_mkhomedir.so, but I don't see anyone else with my problem. Do others just not care that a bunch of extra folders with the machine names are getting created, or is it not happening for anyone else, and I have just done something wrong? RHEL 3.04 samba 2.0.14a-1 Barry Smoke Network Administrator AR Division of Leg. Audit -----Original

Hola: Si aún hay alguien que no está de vacaciones, igual me pueden ayudar. Quiero ajustar unos modelos: REG_LOG <- glm (low ~ X, family = "binomial", data = DATOS) Ejemplo: library(MASS) data(birthwt, package="MASS") birthwt$low <- factor(birthwt$low) birthwt$race <- factor(birthwt$smoke) REG_LOG <- glm (low ~ smoke, family =

Hello, This is the fitted model: > fit Call: multinom(formula = resp ~ pred$cls + pred$smoke) Coefficients: (Intercept) pred$cls2 pred$cls3 pred$cls4 pred$cls5 pred$smoke2 pred$smoke3 Proteinuria -1.140520 0.1616644 0.05554898 -0.01584927 0.02574805 -0.4057245 -0.2898425 Hypertension -2.691215 -0.3699690 -0.22582107 0.01615898 0.26318005 0.1239051 0.2413282

All, Thanks to Nigel, this is now deployed, and any new patches referencing github (ie, new features) need the 'DocApproved' and 'SpecApproved' label. Regards, Amar On Mon, Apr 2, 2018 at 10:40 AM, Amar Tumballi <atumball at redhat.com> wrote: > Hi all, > > A better documentation about the feature, and also information about how > to use the features are one