similar to: nls

I am running the following nls equation. I tried it with data that excel was fitting and got the error: singular gradient matrix at initial parameter estimates I thought it was due to a low number of points (6), but when I create a dataset, I get the same problem. If I remove the parameter "a," then it can find a solution. Does anyone know what I can do to fit this model?

hi all, i am using a dcc model for my senior thesis, it looks at stock returns during times of market uncertainty. my current rfile is below. library(SparseM) library(quantreg) library(zoo) library(nortest) library(MASS) library(fEcofin) library(mvtnorm) library(ccgarch) library(stats) library(foreign) #dataset<-read.csv(file="xxxx",header=FALSE) attach(dataset);

On 05/04/2019 09:37, Simon Pilgrim via llvm-dev wrote: > On 04/04/2019 14:11, Sander De Smalen wrote: >> Proposed change: >> >> ---------------------------- >> >> In this RFC I propose changing the intrinsics for >> llvm.experimental.vector.reduce.fadd and >> llvm.experimental.vector.reduce.fmul (see options A and B). I also >> propose renaming

Hi R forum, Each row of my data (below) show a new contact event between animals. In order to ultimately look at the patterns of intervals between contacts, I need to calculate a contact end time. The contact starts at the date and time shown in V4 and V5, and lasts for the duration shown IN SECONDS in V6: > data2<- read.csv(file=file.choose(), header=F, sep=" ") >

I am having trouble understanding results I'm getting back from coxph doing a recurrent event analysis. I've included the model below and the summary. In some cases, with minor variations, the Robust variance and Wald tests are significant, but the individual covariates may or may not be significant. My main question is: If Wald and robust tests both take into account the

G'day I'm currently using NUT on Debian squeeze box in the same subnet with an IBM 3000 HV (branded Eaton 5125 with Web/SNMP card), now I wanted to get our storage appliance running NexentaStor 3.1 set up to be using NUT too. Nexenta- Stor is an OpenSolaris / illumos-based appliance OS currently using NUT packages from ubuntu hardy. My question here is whether I'm running into a -

WARNING: This is not compatible with the previous lz4 patchset. If you''re using experimental compression that isn''t in mainline kernels, be prepared to backup and restore or decompress before upgrading, and have backups in case it eats data (which appears not to be a problem any more, but has been during development). These patches add lz4 and lz4hc compression

Dear R-users, I have written the following code to generate some trellis plots. It works perfectly fine except that it is quite slow when it is apply to my typical datasets (over several thousands of lines). I believe the problem comes from the loops I am using to subset my data.frame. I read in the archives that the tapply function is often more efficient than a loop in R. Unfortunately ,

Dear all, I have made couple logistic regressions, what making a distribution of some event. Currently, i store it like this: o1 <- lrm(...) o2 <- lrm(...) o3 <- lrm(...) ... Then, i have made a function to peak required regression object from this variables by it number: get_object <- function(obj_name, nModel) { eval (parse(text=paste("o <- ", obj_name, nModel,

Unfortunately there's no sure-fire way to distinguish a sched "op" from regular ones. They happen purely based on position. So for disassembly, use the byte position in the file to determine whether the current op should be decoded as sched or as regular. For assembly, we go back to using a shared table. Ideally we would pick out which one to use based on the position in the

Hi all! I would like to import a matlab or gauss code to R. Could you help me? Bye, Sebasti?n. 2007/6/23, r-help-request en stat.math.ethz.ch <r-help-request en stat.math.ethz.ch>: > Send R-help mailing list submissions to > r-help en stat.math.ethz.ch > > To subscribe or unsubscribe via the World Wide Web, visit >

I have a function "eval.delta" which does what I want but isn't very elegant. I have consulted the R documents, MASS, and S Programming. Is there a practical way to optimize the code? Thank you very much. Peter B. Function: eval.delta <- function(delta){ cat("VALUES\n") vlr <- NULL k <- 0 for(j in 1:length(delta)) if(delta[j] <= 2){

Hi Stepan, Sorry for the delay. It's great that you are working on MergeFunctions as well and I agree, we should definitely try to combine our efforts to improve MergeFunctions. Just to give you some context, the pass (with the similar function merging patch) is already being used in a production setting. From my point of view, it would be better if we focus on improving its capability

Hello Sean and Tobias, Sean, Thank you. Could you describe Nick's ideas in few words or give me links to your discussion, so I could adapt my ideas to it. Tobias, Your patch fails on several modules in my benchmark (73 of ~1800 tests). I have sent one as attachment. See statistics files for more details, all the .ll files you could simply find in test-suite object directory (after