similar to: Help needed with numericDeriv and optim functions

I fit my CDF to sum of exponentials and now I want to take the numerical derivative of this function to obtain probability density.I will really appreciate your help reagrding the error messages I am getting which I don't understand. * * > fitterma <- function(xtime) { a <- -0.09144115 b <- -0.01335756 c <- -2.368057 d <- -0.00600052

Hello: In the example below (or for a censored data) using survfit.coxph, can anyone point me to a link or a pdf as to how the probabilities appearing in bold under "summary(pred$surv)" are calculated? Do these represent acumulative probability distribution in time (not including censored time)? Thanks very much, parmee *fit <- coxph(Surv(futime, fustat) ~ age, data = ovarian)*

Hello All, Does anyone know why length(fit1$time) < length(fit2$n) in survfit.coxph output? Why is the predicted time length is not the same as the number of samples (n)? I tried: example(survfit.coxph). Thanks, parmee > fit2$n [1] 241 > fit2$time [1] 0 31 32 60 61 152 153 174 273 277 362 365 499 517 518 547 [17] 566 638 700 760 791

I have to compute some standard errors using the delta method and so have to use the command "numericDeriv" to get the desired gradient. Befor using it on my complicated function, I've done a try with a simple exemple : x <- 1:5 numericDeriv(quote(x^2),"x") and i get : [1] 1 8 27 64 125 216 attr(,"gradient") [,1] [,2] [,3] [,4] [,5] [,6] [1,] Inf

Thanks; definitely a bug. I've submitted it to the bug tracker at https://bugs.r-project.org/bugzilla/show_bug.cgi?id=17831 Best, luke On Mon, 15 Jun 2020, Raimundo Neto wrote: > Dear R developers, > > I've run into a weird behavior of the numericDeriv function (from the stats > package) which I also posted on StackOverflow (question has same title as > this email,

> On only ten points, what did you expect ? Even with 1000 > observations, estimating a density is difficult, and has > been the subject of a century of research. Kernel density > estimates are among the most successful. For your immediate > application, try plot(density(rnorm(10)), type="l"), etc. wait, you misunderstood me! I'd like to see 10 or 9 points with

Hi, I am stuck on something for a couple days, I am almost about to give up. This looks simple, but I can't figure out. I hope I can get some help here. I am trying to do some symbolic and numerical derivations. Let me explain the problem. Let's say, I have a matrix as follows: > load <- matrix(c(3,0,1,4,1,3),nrow=3,ncol=2,byrow=TRUE) > > load [,1] [,2] [1,] 3 0

Hi All, following expression: x <- sort(rnorm(10)); e <- ecdf(x); d <- numericDeriv(e(x),"x"); makes d far from approximation of one dimensional pdf. What's wrong then here? Kind regards. --------------------------------------------------------------------------- Valery A.Khamenya Bioinformatics Department BioVisioN AG, Hannover

Dear Prof. Brian Ripley, first of all thank you for your answer, I do appreciate how do you manage to keep successfully all your activities and answer posts in this forum! > An empirical CDF is a step function: it does not have a > derivative at the jump points, and has a zero > derivative everywhere else. of course! Let me add few words concerning my simple motivation. 1.

Dear R developers, I've run into a weird behavior of the numericDeriv function (from the stats package) which I also posted on StackOverflow (question has same title as this email, except for the version of R). Running the code bellow we can see that the numericDeriv function gives an error as the derivative of x^a wrt a is x^a * log(x) and log is not defined for negative numbers. However,

Moved from r-help: On Thu, 14 Aug 2003 09:08:26 -0700, Spencer Graves <spencer.graves@pdf.com> wrote : >p.s. The following command in S-Plus 6.1 seems to work fine but >produces an error in R 1.7.1: > >nls(y~a, data=tstDf, start=list(a=1)) >Error in nlsModel(formula, mf, start) : singular gradient matrix at >initial parameter estimates This looks like a bug in

R Help List -- I have defined two time-series-vector-valued-functions, let them be f and g, and want to find the numeric derivative of f with respect to the variable x where f depends on x through g: (d/dx)(f (g(x) ) Moreover, x is a vector I tried this out the long way (naming every element of the x vector and then making the 'theta' argument in numericDeriv() the character vector of

Dear all As far as I could trace, looking at the function C function numeric_deriv, this unwanted behavior comes from the inner most loop in, at the very end of the function, for(i = 0, start = 0; i < LENGTH(theta); i++) { for(j = 0; j < LENGTH(VECTOR_ELT(pars, i)); j++, start += LENGTH(ans)) { SEXP ans_del; double origPar, xx, delta; origPar = REAL(VECTOR_ELT(pars, i))[j];

Hi, I am a non-expert user of R. I am essaying the fit of two different functions to my data, but I receive two different error messages. I suppose I have two different problems here... But, of which nature? In the first instance I did try with some different starting values for the parameters, but without success. If anyone could suggest a sensible way to proceed to solve these I would be

This message is in MIME format --_=XFMail.1.3.p0.Linux:990702182137:16900=_ Content-Type: text/plain; charset=us-ascii There was some discussion a while back on R-devel between Ross Ihaka, Paul Gilbert and myself about row subsetting in time series. I think the consensus was that "[.ts" should not try to coerce its result back to a time series object (which is underlying the problem

Dear All, I am trying to solve a Generalized Method of Moments problem which necessitate the gradient of moments computation to get the standard errors of estimates. I know optim does not output the gradient, but I can use numericDeriv to get that. My question is: is this the best function to do this? Thank you Jean,

Isolate some of the non-VMI timer related changes in Linux. This patch moves the cyc_2_ns conversion code into a common location, eliminating redundant code in hpet and tsc timer implementations, and introduces some macros that may be redefined by the sub-architecture to avoid dependence on APIC routing, CMOS time sync, and testing for broken time hardware (which presumably, does not happen in a

Isolate some of the non-VMI timer related changes in Linux. This patch moves the cyc_2_ns conversion code into a common location, eliminating redundant code in hpet and tsc timer implementations, and introduces some macros that may be redefined by the sub-architecture to avoid dependence on APIC routing, CMOS time sync, and testing for broken time hardware (which presumably, does not happen in a

In a virtualized environment, virtual machines will time share the system with each other and with other processes running on the host system. Therefore, a VM's virtual CPUs (VCPUs) will be executing on the host's physical CPUs (pcpus) for only some portion of time. The VMI exposes a paravirtual view of time to the guest operating systems so that they may operate more effectively in a

In a virtualized environment, virtual machines will time share the system with each other and with other processes running on the host system. Therefore, a VM's virtual CPUs (VCPUs) will be executing on the host's physical CPUs (pcpus) for only some portion of time. The VMI exposes a paravirtual view of time to the guest operating systems so that they may operate more effectively in a