similar to: Spearman correlation ties and discrepancies

I'm wondering how odds ratio is computed. I thought that it is (n11/n12)/(n21/n22), but it is not what fisher.test() computes. Could somebody let me know? > n11=3 > n12=1 > n21=1 > n22=3 > > n1_=n11+n12 > n2_=n21+n22 > > n_1=n11+n21 > n_2=n12+n22 > > x=rbind(c(n11,n12),c(n21,n22)) > > threshold=dhyper(n11,n1_,n2_,n_1) >

Hi, I'm trying to use the FEC feature. I have a service which does the encoding with OPUS_SET_INBAND_FEC(1) and OPUS_SET_PACKET_LOSS_PERC(20) with 10ms packets. I'm not clear on the decoding process though. 1- When a packet is lost, do I need to call decode with fec=1 ONLY or do I need to call decode with fec=0 after as well? 2- How do I know up front the size of the pcm that I send to

I am a new R user, and am looking to call Postgres through R. I am not so technical and need help in setting up. I have downloaded the tar file but cannot get passed this step. Is there documentation for dummies to get working with this? I don't even know where I should save this file? [[alternative HTML version deleted]]

Hi, I would consider the calculation of r-squared in the following to be a bug, but then, I've been wrong before. It seems that R looks to see if the model contains an intercept term, and if it does not, computes r-squared in a way I don't understand. To my mind, the following are two alternative parametrizations of the same model, and should yield the same r-squared. Any insight much

Hello R-Users,   I have one binary dependent variable and a set of independent variables (glm(formula,…,family=”binomial”) ) and I am using the function stepAIC (“MASS”) for choosing an optimal model. However I am not sure if stepAIC considers significance properties like Likelihood ratio test and Wald test (see example below).     > y <- rbinom(30,1,0.4) > x1 <- rnorm(30) > x2

On Jan 4, 2011, at 7:45 AM, arrowdodger wrote: > Hello. I see many discrepancies in config.h file generated by CMake and autoheader. > > Most of them are following: > In autofoo-generated config: > /* Define to 1 if you have the `<name>' function. */ > #define HAVE_<name> 1 > but in CMake-generated: > #undef HAVE_<name> > This happens because in

arrowdodger <6yearold at gmail.com> writes: >> Or to say it with other words: patches welcome. > > So, how should i proceed? Make CMake-generated config to be identical to > autotools one? That would be a good thing. Please note that some checks are a bit tricky. A function that on platform A is on header foo.h on another platform may be on bar.h. Furthermore, cmake's

Eric Christopher <echristo at apple.com> writes: >>> Or cleanup both headers from unused stuff by Eric's >>> suggestion? >> >> I'm not sure this is a good idea (not that it is bad either). Murphy's >> Law says that a function that you remove today will be used tomorrow. > > I meant literally functions that aren't used in the

> contains most of them. If they're non-trivial (like the ones I needed to > add for OSX functionality) that's a different story. FWIW the difference is even more significant on, e.g. mingw32 because process spawning is pretty much expensive and sometimes configure time dominates the compile time :) -- With best regards, Anton Korobeynikov Faculty of Mathematics and Mechanics,

Okay, i've started slowly working. Who can i send patches for review, when they will be ready? -------------- next part -------------- An HTML attachment was scrubbed... URL: <http://lists.llvm.org/pipermail/llvm-dev/attachments/20110106/88a7e893/attachment.html>

Hello. When i run llvm-config --libs jit bitreader bitwriter ipo linker engine i get: -lLLVMX86Disassembler -lLLVMX86AsmParser -lLLVMX86CodeGen -lLLVMSelectionDAG -lLLVMAsmPrinter -lLLVMMCParser -lLLVMX86AsmPrinter -lLLVMX86Utils -lLLVMX86Info -lLLVMLinker -lLLVMArchive -lLLVMipo -lLLVMBitWriter -lLLVMBitReader -lLLVMJIT -lLLVMExecutionEngine -lLLVMCodeGen -lLLVMScalarOpts -lLLVMInstCombine

Looks like constants in include/llvm-c/Core.h aren't in sync with enums. For example, LLVMAdd is 8 in Core.h and llvm::Instruction::LLVMAdd evaluates to 9 in C++. Same for Cast Operators section and possibly in other places. Also, llvm/Support/TargetRegistry.h and llvm/Target/TargetRegistry.h define two different version of some classes, particularly llvm::Target. Fields with the same

On Sat, Sep 17, 2011 at 9:14 PM, Yuri <yuri at rawbw.com> wrote: > Looks like constants in include/llvm-c/Core.h aren't in sync with enums. > For example, LLVMAdd is 8 in Core.h and  llvm::Instruction::LLVMAdd > evaluates to 9 in C++. > Same for Cast Operators section and possibly in other places. Yes; we don't make any sort of guarantee about that, and such a guarantee

On 09/17/2011 21:53, Eli Friedman wrote: > Yes; we don't make any sort of guarantee about that, and such a > guarantee is not necessary for correctness. Aren't values in Core.h supposed to be used by users of API and they should match enums, or what they are for then? What are they matched against? >> > Also, llvm/Support/TargetRegistry.h and

I posted a question on stackoverflow dealing with determining elemental existence in a vector, and to my surprise, the method that was brutally slow for me on my PC was insanely fast on one of the member's platform (he was running Linux). You can view the details here. http://stackoverflow.com/questions/33453141/most-efficient-way-to-determine-if-element-exists-in-a-vector I didn't know

Hi, I do want to use the Mann-Whitney test which ranks my data and then uses those ranks rather than the actual data. Here is the R code i am using: group1<- c(1.34,1.47,1.48,1.49,1.62,1.67,1.7,1.7,1.7,1.73,1.81,1.84,1.9,1.96,2, 2,2.19,2.29,2.29,2.41,2.41,2.46,2.5,2.6,2.8,2.8,3.07,3.3) > group2<-

Hello I would like to develop the use of R. Trying R and more particulary the cox model, I am surprised by discrepancies between results with stata and R for a cox model With the same data base, I get a hazard ratio (4.82) that is not the same obtained with stata (4.52) You will find attached the file leukemia.dta I used (Stata) Here are the codes for R library(foreign)

I have been using R and SAS from past 6 months and i found a interesting thing while doing PLS in R and SAS is that when we use NO SCALE option in SAS and scale=FALSE in R , we see the estimates are matching but if we use scaling option in SAS and R the estimates differ to greater extent , you can try with any data set we will get very different estimates while using the scaling option. can any

Dear all, I encounter some discrepancies when comparing the deviance of a weighted and unweigthed model with the AIC values. A general example (from 'nls'): DNase1 <- subset(DNase, Run == 1) fm1DNase1 <- nls(density ~ SSlogis(log(conc), Asym, xmid, scal), DNase1) This is the unweighted fit, in the code of 'nls' one can see that 'nls' generates a vector

> > We may just not use those functions anymore - do you have a list of these? > Yes, i've started to make up a list of those functions, but it haven't finished yet. > This is more concerning - maybe it's a windows specific problem that came > along? > Not sure, i haven't look yet for CMake checking code itself. By the way, i'm using FreeBSD. Or to say it