similar to: new package: eha

A new version of 'eha' (0.92-1) is now on CRAN. From the ChangeLog: 0.92-1 (January 7, 2004) * mlreg: Geometric distribution (i.e., constant baseline discrete hazard) added. Not for frailty models, yet (on the TODO list). * mlreg: New argument, 'n.points', added to 'control'. Controls the number of points used in the Gauss-Hermite quadrature. * mlreg: Stricter

A new version of 'eha' (0.92-1) is now on CRAN. From the ChangeLog: 0.92-1 (January 7, 2004) * mlreg: Geometric distribution (i.e., constant baseline discrete hazard) added. Not for frailty models, yet (on the TODO list). * mlreg: New argument, 'n.points', added to 'control'. Controls the number of points used in the Gauss-Hermite quadrature. * mlreg: Stricter

Now I try to add some C and Fortan code to my package, so the NAMESPACE file is useDynLib(eha) importFrom(survival, Surv) export(mlreg.fit, risksets) but I get ..... * checking R files for library.dynam ... OK * checking S3 generic/method consistency ... WARNING Error in .try_quietly({ : Error in library(package, lib.loc = lib.loc, character.only = TRUE, verbose = FALSE) :

A new version (0.96.3) of the package 'eha' is now on CRAN. Apart from some bug fixes, there are some news. The most noteworthy are: (i) 'plot.Surv' has a few new options, (ii) 'weibreg' now can fit null models (i.e., only scale and shape) and covariates are no longer automatically centered (although this is still the default), (iii) there is a new function,

Hi, I would like to fit parametric survival models to time-to-event data that are left truncated. I have checked the help page for survreg and looked in the R-help archive, and it appears that the R function survreg from the survival library (version 2.16) should allow me to take account of left truncation. However, when I try the command

Dear R-users, I need to use the aftreg function in package 'eha' to estimate failure times for left truncated survival data. Apparently, survreg still cannot fit such models. Both functions should be fitting the accelerated failure time (Weibull) model. However, as G?ran Brostr?m points out in the help file for aftreg, the parameterisation is different giving rise to different

Dear List, After including cluster() option the coxreg (from eha package) produces results slightly different than that of coxph (from survival) in the following time-dependent treatment effect calculation (example is used just to make the point). Will appreciate any explaination / comment. cheers, Ehsan ############################ require(survival) require(eha) data(heart) # create weights

I am unsure what is being returned, and what is supposed to be returned, when using 'predict' with "type='expected'" for an aftreg survival model. The code below first generates a weibull model, then uses predict to create a vector of the linear predictors, then attempts to create the 'expected' vector, which is empty. The final two steps in the code generate a

"Error in predict.coxph(f.ph.eha, newdata = mort, type = "lp") : Data is not the same size as it was in the original fit" This error message was added in a recent update to predict.coxph. If it needs to reconstruct some aspects from the original fit, such as the X matrix or strata vector, it makes sure that the data set is the same size. It was to stop fit <-

Dear useRs, I am currently fitting an advanced failure time model using G?ran Brostr?m's excellent "eha" library with the "aftreg" command. My question: How do I interpret the "Overall p-value", that is reported at the very bottom of the output? I already figured out it must be a chi-square test, but I am wondering what a p-value < 0.01 means: Does it mean

G?ran, thanks for the update, I'm just about to install it! Just wanted to drop you a short line about performance (as you once requested): aftreg takes ages on my windows machine to calculate a small set of 7 observations which are not even grouped together by "id". To be a bit more precise, it takes 2:40 mins on my Intel T9300 Core2 Duo @ 2.5 GHz. Bigger samples with about 700

As stated in the design paragraph, this design does not intend to model precise CFG at instruction level since it’s complicated and unnecessary. As long as we comply C and C++ rules listed below, we achieve -EHa semantic. There is NO need to precisely model HW exception control flow at instruction-level. Your example about memcpy() is just a bug in current implementation. I will fix it so that

Dear All, I would like to fit some parametric survival models using left truncated, right censored data in R. However I am having problems finding a function to fit parametric survival models which can handle left truncated data. I have tested both the survreg function in package survival: fit1 <- survreg(Surv(start, stop, status) ~ X + Y + Z, data=data1) and the psm function in package

Resending; I accidentally dropped llvm-dev. -Eli From: Eli Friedman Sent: Wednesday, April 1, 2020 1:01 PM To: Ten Tzen <tentzen at microsoft.com> Cc: aaron.smith at microsoft.com Subject: RE: [EXT] [llvm-dev] [RFC] [Windows SEH] Local_Unwind (Jumping out of a _finally) and -EHa (Hardware Exception Handling) This looks like it outlines the implementation pretty well. For goto in finally,

* When a goto in a _finally occurs, we must "unwind" to the target code, not just "jump" to target label I'm not sure what you're trying to say here. In the Microsoft ABI, goto out of a catch block also calls into the unwinder. We have to run any destructors, and return from the funclet (catchret/cleanupret). * The call inside a _try is an invoke with EH

Hi, This is a spin-off of previous Windows SEH RFC below. This RFC only focus on supporting HW Exception Handling. A detailed implementation can be seen in here: https://github.com/tentzen/llvm-project/commit/8a2421c274b683051e456cbe12c177e3b934fb5e It passes all MSVC SEH suite (excluding those with “Jumping out of _finally” ( _Local_Unwind)). Thanks, --Ten **** The rules for C code: ****

Dear mailing list, I'm trying to run the sample program about coxreg in the eha package. But the command is not recognized. I tried the boot and also the survival library. Hope you can help me solve this little problem. Thank you. Jei ---------------------------------------------------------------- This message was sent using IMP, the Internet Messaging Program. University of the

Hi, all, The intend of this thread is to complete the support for Windows SEH. Currently there are two major missing features: Jumping out of a _finally and Hardware exception handling. The document below is my proposed design and implementation to fully support SEH on LLVM. I have completely implemented this design on a branch in repo:

Hi, Eli, Why are you under the impression that threw_exception() will not be called if optimizations are enabled? I don’t know if the -EHa Spec is clearly described in MSFT Webs. At least this proposal has described the rules for both C & C++ code. The very first rule clearly said that “no exception can move in or out of _try region., i.e., no potential faulty instruction can be moved

Reply inline From: Ten Tzen <tentzen at microsoft.com> Sent: Wednesday, April 1, 2020 3:54 PM To: Eli Friedman <efriedma at quicinc.com>; llvm-dev <llvm-dev at lists.llvm.org> Cc: aaron.smith at microsoft.com Subject: [EXT] RE: [llvm-dev] [RFC] [Windows SEH] Local_Unwind (Jumping out of a _finally) and -EHa (Hardware Exception Handling) ? For goto in finally, why are you