similar to: Any R function for self-controlled case series method /effect absorption?

Hi all I have another GLIM question. I have been using R as well as Genstat (version 6) in order to fit GLIM models to the data (displayed below). The same models are fitted but the answers supplied by the two packages are not the same. Why? Can anyone help? A discription of the data and the type of model/s fitted can be found below. Regards Allan The

Hello, I have a simple question that I could not really figure out. I am plotting labels within a graph using the text function. I first plot the first label by specifying the x and y coordinates on the graph. Then to plot the second label next to it, I am using te strwidth function to get the width of the previous label in user coordinate then add the maximum width to the x value. However, this

Hello All, While trying to install Matrix package following error message came out: /usr/bin/ld: cannot find -lblas-3 collect2: ld returned 1 exit status make: *** [Matrix.so] Error 1 ERROR: compilation failed for package 'Matrix' ** Removing '/usr/lib/R/library/Matrix' ** Restoring previous '/usr/lib/R/library/Matrix' It seems that someting is missing. Have anybody

I would really appreciate it if someone can give suggestions on how to do spectra fitting in R using ordinary least square fitting and non-negativity constraints. The lm() function works well for ordinary least square fitting, but how to specify non-negativity constraints? It wouldn't make sense if the fitting coefficients coming out as negative in absorption spectra deconvolution. Thanks.

Hey everyone, I know I've come across this somewhere, in either the blue or white books or in one of the help docs but I can't put my hand on it. What's the name of the statistical notation used in R? responseVar ~ anExplantory:anotherExplantory + thridExplantory Is this part of a coherent framework of notation that is as applicable to models which are not generalized linear models

Hi Everyone, I am using R 2.10.1. lmer function works properly, however pvals.fnc () does not despite the fact that I uploaded: - library(lme4) - library(coda) - library(languageR) This is the error message I get pvals.fnc(lexdec3.lmerE2, nsim=10000)$fixed Error in pvals.fnc(lexdec3.lmerE2, nsim = 10000) : MCMC sampling is not yet implemented in lme4_0.999375 for models with random

Does anyone know if there is a package or other method of reading Genstat files directly into R. Genstat isn't listed in the foreign package. Many thanks, Graham [[alternative HTML version deleted]]

This is a very fascinating discussion topic. I find I run into some fundamental differences in interpretation of the phrase "statistical computing". I think of it as writing programs or functions, such as R or packages in R, and of understanding the numerical analysis behind these functions. I exclude USING computer programs, such as R, for data analysis from my definition of

Hi all I'm doing some things with a colleague comparing different sorts of models. My colleague has fitted a number of glms in Genstat (which I have never used), while the glm I have been using is only available for R. He has a spreadsheet of fitted means from each of his models obtained from using the Genstat "predict" function. For example, suppose we fit the model of the type

Hello, Any help on the following issue will be appreciated. How do I delete files or directories in my first level of directory that is specified as host. Here is an example : rsync -avz --delete ${SOURCE_HOST}:/mlinkfam/extract/sccs/pa/* /mlinkfam/extract/sccs/pa Giving above command I find redundant files or directory not getting deleted from the first level of target directory

I would like to do a logistic multiple regression on a binary variate, with what Genstat calls an offset, ie a regression variable with the coefficient constrained=1. I'm far from home and have Splus but not R here, but any information from either source would be very welcome. I'd hate to have to go back to using Genstat . . . Thanks, Ted. --------------- Dr E.A. (Ted) Catchpole

I have a FunctionPass F that needs a list of all the SCCs for use in its doFinalization() method. Let's say I write a CallGraphSCCPass C that creates an array of all SCCs. Let C be required by F, and let F call getAnalysis<C>() from its doFinalization() method. Am I guaranteed that C's runOnSCC() method will have executed on all SCCs before F's doFinalization() method?

Hi, I am using the scc_iterator class in my code on a CallGraph, where some functions are not called from within the module. It seems that scc_iterator does not list all SCCs if the graph is not connected; only those nodes connected to the node pointed to by GraphTraits<...>::getEntryNode() are returned. Can someone verify this behavior? Any tips on how I should go about extending the

I shouldn't try to do this on Monday morning. Can anyone suggest why the make for R 0.63 is failing for me under Solaris (SunOS 5.6). Paul Gilbert ... creating src/scripts/html2dos creating tests/Makefile creating tests/Examples/Makefile creating src/include/Platform.h R is now configured for sparc-sun-solaris2.6 Source directory: . Installation directory: /usr/local C

Hi, I know that is not possible make a stepwise procedure using REML in R, I can use ML for this. For nested design it may be very dangerous due the difference in variance structure, mainly in a splitplot design. ML make significative variables that REML dont make. I read an article that is made a stepwise procedure using GENSTAT. from article: "Terms were dropped from a model in a

Hey all, I'm working on adding function attribute propagation to function summaries in the ThinLTO index, and have run into some trouble with ensuring bottom-up traversal when finding the SCCs in the call graph. I'm basing my implementation for the GraphTraits for the ModuleSummaryIndex off the GraphTraits<CallGraph *> implementation (

Hi R-help members, I have read a lot in the Archive about the "Type I" vs "Type III" sum of square. I think I have read confusing post so I want to have a clear idea of the problem. Here is an example. I have 3 groups of subjects of unequal sample size (G1 (n=7), G2 (n=7), G3 (n=4)). for Each subject I have 4 measures corresponding to the crossing of 2 factor (A & B)

I ran across an interesting case and wanted to share it. I'm not proposing any particular changes, but the experience seemed interesting to discuss. First, a bit of background. An LLVM Loop models a specific type of cycle in the CFG. Not all cycles are Loops. Many of our optimization transforms are phrased over loops, which means that a non-loop cycle tends to be less well optimized.

>From the fedora 19 host: [root@fedora ~]# sg_inq /dev/sdc standard INQUIRY: PQual=0 Device_type=0 RMB=0 version=0x05 [SPC-3] [AERC=0] [TrmTsk=0] NormACA=0 HiSUP=0 Resp_data_format=0 SCCS=1 ACC=0 TPGS=1 3PC=0 Protect=0 [BQue=0] EncServ=0 MultiP=0 [MChngr=0] [ACKREQQ=0] Addr16=0 [RelAdr=0] WBus16=1 Sync=1 Linked=0 [TranDis=0] CmdQue=1 length=36 (0x24)

Hi all, I have one analysis pass that I want to perform on call graph SCCs. However, for each function in the SCC, I need function-level analyses, like the dominator tree and the memory dependency analysis. I’ve been told before <http://stackoverflow.com/questions/30059622/using-dominatortreewrapperpass-in-callgraphsccpass> that these were not available from a CallGraphSCCPass. What would