similar to: Box's M/likelihood ratio test for equal v-c matrices

Hello: Please help me through my confusion. I am having trouble reconciling the difference between what I believe is the conventional definition of an odds ratio for a 2-by-2 table and the output produced by fisher.test() in R. Consider the following example: > Discrim <- matrix(c(1,10,24,17), + nr = 2, + dimnames = list(AGE = c('young', 'old'), +

Hello, I am using WinXP, R version 2.3.1, and SAS for PC version 8.1. I have mostly used SAS over the last 4 years and would like to compare the output of PROC DISCRIM to that of lda( ) with respect to a very specific aspect. My data have k=3 populations and there are 3 variates in the feature space. When using using the code PROC DISCRIM DATA = FOO OUT = FOO_OUT OUTSTAT = FOOSTAT

Pass to --commands-from-file the name of a file containing customization commands in each line, as if they were specified as command line arguments. This eases the reuse of commands among different builder/customize/sysprep invocations. --- builder/cmdline.ml | 3 +- customize/customize_run.ml | 5 +++ generator/customize.ml | 98 ++++++++++++++++++++++++++++++++++++++++++++-- 3

Dear all I was wondering whether such a long post could be fortune-ed. What do you think? Regards Liviu On Sat, Aug 21, 2010 at 9:33 PM, Sharpie <chuck at sharpsteen.net> wrote: > Well, I can think of three ways it can go down: > > > 1. ?You want a shiny new pony. > > You ask about it on the mailing list and it seems that everyone else in the > world responds

Which version of openafs do I need to compile AFS support into samba. I tried compiling Samba 3.0.7 but get a setpag() undefined error, when building against OpenAFS 1.2.11. Thanks, Derek Isn't sanity just a one-trick pony anyway? I mean, all you get is that one trick, rational thinking, but when you're good and crazy, well, the sky's the limit! "The Tick (comic book)"

I am trying to write the following code in R. The code works in S+ and i am trying to do the program in R. x=discrim(admit~gpa+gmat,prior=c("uniform"),data=data.mm) i wrote the following in R: x=lda(admit~gpa+gmat,data=data.mm) i could not figure out how to write prior=c("uniform") in R. I would get an error every time. I think that it has something to do with

Add a new Getopt module to mllib, to parse command line arguments with handlers close to the ones used with Arg, but using getopt(3) (actually getopt_long_only) to do the real parsing. This allow us to provide options for OCaml tools with a syntax similar to the C tools, and use the additional features getopt offers and Arg does not. Do a single-step conversion of Common_utils and all the OCaml

Hello R people I now know how to run my discriminant analysis with the lda function in MASS: lda.alain=lda(Groupes ~ Ht.D0 + Lc.Dc + Ram + IDF, gr, CV = FALSE) and it works fine. But I am missing a test and cannot find any help on how to get it, if it exist. The "S" equivalent: discrim(structure(.Data = Groupes ~ Ht.D0 + Lc.Dc + Ram + IDF, class = "formula"), data = gr,

Dear LLVM community, I am affiliated with the design and development of the Pony<http:/www.ponylang.org> programming language, which was recently published and has since been discussed on hacker news<https://news.ycombinator.com/item?id=9482483>, reddit [1]<http://www.reddit.com/r/ponylang>

Hi. I'm running dovecot 1.0.rc7 in a RHEL. I need to know if this version supports IMAPV4 rev1 and IDLE for a new project. Thanks. [root at pony mail]# uname -a Linux pony.sabeco.es 2.6.18-1.2798.fc6 #1 SMP Mon Oct 16 14:37:32 EDT 2006 i686 i686 i386 GNU/Linux [root at pony mail]# dovecot --version 1.0.rc7 [root at pony mail]# dovecot -n # /etc/dovecot.conf login_dir:

Add simple operations for RHEL guests using subscription-manager, so it is possible to e.g. install software on them. --- builder/Makefile.am | 1 + builder/virt-builder.pod | 47 ++++++++++++++++++ customize/Makefile.am | 2 + customize/customize_run.ml | 34 +++++++++++++ customize/subscription_manager.ml | 53 ++++++++++++++++++++

Hi! Will you please ask a newbie's question? Need linear discriminant analysis, need to capture discrim. function coefficiemts for further processing. Using R ver 1.4.0 package MASS function lda() Help says resulting object should have "components" (among others): means, scaling, svd, but program returns NULL for all of them Thank you!

Hi I am trying to understand how to get the validate() function in Design to work with the subset option. I tried this: ovarian.cph=cph(Surv(futime, fustat) ~ age+factor(ecog.ps)+strat(rx), time.inc=1000, x=T, y=T, data=ovarian) validate(ovarian.cph) #fine when no subset is used, but the following two don't work: > validate(ovarian.cph, subset=ovarian$ecog.ps==2) Error in

Dear All, I have just estimated this model: ----------------------------------------------------------- Logistic Regression Model lrm(formula = Y ~ X16, x = T, y = T) Model Likelihood Discrimination Rank Discrim. Ratio Test Indexes Indexes Obs 82 LR chi2 5.58 R2 0.088 C 0.607 0

On Fri, Jun 24, 2016 at 05:42:37PM +0200, Pino Toscano wrote: > Add a new Getopt module to mllib, to parse command line arguments with > handlers close to the ones used with Arg, but using getopt(3) (actually > getopt_long_only) to do the real parsing. This allow us to provide > options for OCaml tools with a syntax similar to the C tools, and use > the additional features getopt

Hi, I am trying to run a simple logistic regression using lrm() to calculate a odds ratio. I found a confusing output when I use summary() on the fit object which gave some OR that is totally different from simply taking exp(coefficient), see below: > dat<-read.table("dat.txt",sep='\t',header=T,row.names=NULL) > d<-datadist(dat) > options(datadist='d')

Add a new Getopt module to mllib, to parse command line arguments with handlers close to the ones used with Arg, but using getopt(3) (actually getopt_long_only) to do the real parsing. This allow us to provide options for OCaml tools with a syntax similar to the C tools, and use the additional features getopt offers and Arg does not. Do a single-step conversion of Common_utils and all the OCaml

Ms.Karunambigai M PhD Scholar Dept. of Biostatistics NIMHANS Bangalore India ----- Forwarded Message ---- From: karuna m <m_karuna2002@yahoo.com> To: R-help@r-project.org Sent: Thu, 26 May, 2011 10:55:02 AM Subject: likelihood ratio test Dear R-help, Can anybody tell me which R package has Lo-Mendell Rubin LR test and Bootstrap LR test to compare the model fit between k class and k+1

It seems to me that R returns the unpenalized log-likelihood for the ratio likelihood test when ridge regression Cox proportional model is implemented. Is this as expected? In the example below, if I am not mistaken, fit$loglik[2] is unpenalized log-likelihood for the final estimates of coefficients. I would expect to get the penalized log-likelihood. I would like to check if this is as expected.

I'm applying logistic regression to a moderate sized data set for which I believe Wald based confidence intervals on B coefficients are too conservative. Some of the literature recommends using confidence intervals based on the likelihood ratio in such cases, but I'm having difficulty locating a package that can do these. Any help would be immensely appreciated. Best, Jeff Hanna --