similar to: : GLIM PROBLEMS

After some futile searches, I decided to ask the list to see if any of the sages out there would have an answer: I have a function I wrote a few years ago in S, which calls glim numerous times. I'd like to port it to R, but glm works differently from glim, which takes as part of its input an X design matrix. I probably could write a function to convert glim to glm, but hope this

Hi, When I excecute the following command line wine --winver nt40 --dll shlwapi=b --managed -- /nfs2/bin/Xilinx/ise4.1i/bin/nt/par.exe -pl 5 -rl 5 -e 1 -t 1 -w /tmp/design.ncd design.ncd design.pcf the following error message is returned err:seh:EXC_DefaultHandling Unhandled exception code c0000005 flags 0 addr 0x400a5648 but if I run the following command line wine --winver nt40 --dll

Dear Experts, In glim() of S Plus, one of the returned values is "var", the estimated variance matrix of coefficients. However, in glm() of R (there is no glim() in R), "var" is not one of the returned values. Anyone know what could I get the varience matrix of coefficients in glm() in R? As a novice in R and S+, I'd appreciate your help Sincerely, Charlie Liu

Hi all, In my continuous transition of GLIM to R I try to make a glm with binomial errors. The data file have 3 vectors: h -> the factor that is ajusted (have 3 levels) d -> number of animais alive (the response) n -> total number of animals To test proportion of alive, make d/n. In GLIM: $yvar d$ $error binomial n$ $fit +h$ scale deviance = 25.730 (change = -9.138) at cycle 4

Dear All, I wonder if anyone can advise me as to whether there is a consensus as to how the effect size should be calculated from GLIM models in R for any specified significant main effect or interaction. In investigating the causes of variation in infection in wild animals, we have fitted 4-way GLIM models in R with negative binomial errors. These are then simplified using the STEP procedure,

Hello, I would like to know if there is any package that allow us to fit Generalized Linear Models via Maximum Likelihood and Linear Models using Generalized Least Squarse in R as the functions glim and gls, respectively, from S-Plus. Also, anybody know if there is any package that fit Log-Linear Models using Generalized Least Squares? Any help will be very useful. Thanks, -- Frederico

On 2017-11-10 07:47, Nemanja Ivanovic wrote: > One thing I thought about doing a while back and never really wrote a > POC for is the following: > - Make FirstCSRCost a property of the MachineBasicBlock (or create a > map of MBB* -> FirstCSRCost) > > - Implement a pre-RA pass that will populate the map as follows: > > - Identify all blocks with calls > > -

On 2017-11-14 17:22, Quentin Colombet wrote: > Hi, > > I think it is kind of artificial to tie the CSRCost with the presence > of calls. > I think I’ve already mentioned it in one of the review, but I > believe it would be better to differentiate when we want to use a CSR > to avoid spilling or to avoid splitting. CSR instead of spilling is > good, CSR instead of

On 2017-11-17 13:10, Quentin Colombet wrote: >> On Nov 16, 2017, at 2:31 PM, junbuml at codeaurora.org wrote: >> On 2017-11-14 17:22, Quentin Colombet wrote: >> >>> Hi, >>> I think it is kind of artificial to tie the CSRCost with the >>> presence >>> of calls. >>> I think I’ve already mentioned it in one of the review, but I

Hi, Suppose I use the following codes to read in a data set. ############################################### > rating <- scan("../Data/Rating.csv", + what = list( + usage = "", + mileage = 0, + sex = "", + excess = "", + ncd = "", +

Hi, I am a newbie and I have installed Wine release 20000909 on a machine running Mandrake7.2 and win2000. The DefaultLoadOrder for the DLLs are builtin, so, native & elfdll. LD_LIBRARY_PATH and EXTRA_LD_LIBRARY_PATH points to the directory containing the lib*.so files. I encontered the following errors while running a place & route tool.

Hi, I have a medium-sized (19MB) CSV file that I'd like to read into R. The read.csv() function seems to be a bit inefficient to deal with it, and I remember that using scan() with "what" options is better. However I'm unable to understand how to use it. The first few lines of the data look like:

Hi, This may actually be a theoretical question. When I tried to do the following: ########################################################## > colnames(rating.adclms) [1] "usage" "mileage" "sex" "excess" "ncd" [6] "primage" "minage" "drivers" "district" "cargroup" [11]

I'm running Samba 2.0.0 on Solaris 2.5 and 2.6. I've had a report that a user on a Wincenter machine (NT4 + Windows Terminal Server + Citrix Metaframe + NCD stuff) dragged a Word document from his NT fileserver onto one of my Samba servers and the result was filled with zeros. We have been able to reproduce the problem from annother account on the Wincenter machine, but cannot make it

Hi all I try to make a weibull survival analysis on R. I know make this on GLIM, and now I try to make the GLIM exercice GLEX8 on R to learning and compare the test. The variables are: time censor group bodymass In GLIM I make: $calc %s=1 $ to fit weibull rather than exponential $input %pcl weibull $ $macro model group*bodymass $endmac$ $use weibull t w %s $ Then, GLIM estimate an alpha for the

On 2017-10-30 21:20, Hal Finkel wrote: > On 10/30/2017 12:20 PM, junbuml at codeaurora.org wrote: >> On 2017-10-27 19:50, Hal Finkel wrote: >>> On 10/27/2017 03:32 PM, Jun Lim via llvm-dev wrote: >>> >>>> When compiling C code below for AArach64, I saw that shrink-wrapping >>>> didn't happen due to the very early uses of CSRs in the entry

I came to R from GLIM and its glm. My data sets (ecological community data) are severely over-dispersed, and so I was delighted to find out that the MASS library has glm.nb which is an advancement from the GLIM macros I had used (N.E.Breslow, Applied Statistics 33, 38--44; 1984). However, I need to use offset, but that failed. I am not (yet --- hopefully) fluent enough in R to be able to

Hello, Has anyone written R functions for applying self-controlled case series methods (http://statistics.open.ac.uk/sccs/). In fact only thing needed is to modify glm function to allow absorption of effect. Eg. in Poisson model individual effect is used as factor, but it is considered as nuisance term where parameter estimates are not needed. Could anyone point how absorbing individual

I've downloaded R for windows (9.0.1) and it is great! I've converted all my lecture notes for my GLM course to run on R (they are available on my web page below). I must admit I particularly like the default contrast options, which are identical to GLIM. Also I like the gl function - very useful! I have a couple of questions/bugs: 1. predict.glm doesn't work, but predict.lm does -

I want to do a logistic regression without an intercept term. This option is absent from glm, though present in some of the inner functions glm uses. I gather glm is the standard way to do logistic regression in R. Hoping it would be passed in, I said > r <- glm(brain.cancer~epilepsy+other.cancer, c3, > family=binomial(link="logit"), intercept=FALSE) which produced