similar to: AW: numericDeriv and ecdf

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

Hi all, is there any package in R capable of smooth approximation of CDF basing on given sample? (Thus, I am not speaking about ecdf) In particular, I expect very much that the approximation should subject to the property: f(x0)<=f(x1) for x0<x1, where x0 and x1 belong to range of the sample given. Polynomial approximation could be OK for me as well. P.S.

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.

Hi all, once more about the old subj :-) My data has too much various distribution families and for every particular experiment I need just to decide whether the data is "quite homogeneous" or it has two or more clusters. I've revisited the following libraries: amap, clust, cclust, mclust, multiv, normix, survey. And I didn't find any ready-to-use general

> Almost any method of fitting a density estimate would work on > integrating (numerically) the result. it is a nice idea concerning the monotony property, which will be obtained automatically, but I am going to use results of approximation analytically > In particular, look at package polspline, where > p(old)logspline does the integration for you. thank you, I am going to

Hi All, We'd like to use functions provided in R in our application. Our application is written in C/C++ and currently runs on win32, Linux and Mac. We'd be happy to attach the whole R ( i.e. not just transfer some function by hand). It is important that we deal with big amount of data, so "command line"-like invocations won't be very interesting. We'd

Hi All, We'd like to use functions provided in R in our application. Our application is written in C/C++ and currently runs on win32, Linux and Mac. We'd be happy to attach the whole R ( i.e. not just transfer some function by hand). It is important that we deal with big amount of data, so "command line"-like invocations won't be very interesting. We'd

> Well, that is in all good texts on R, together with the > solution: drop=FALSE. See ?"[" for the on-line details. OK. Thank you a lot. Now patched cclust and clustIndex work fine for 1D case. BTW, why not to apply the "drop=F" to these functions? I guess other users need 1D case as well. kind regards, Valery A.Khamenya

Hi All is there "homals" package prepared for win32? kind regards, Valery A.Khamenya --------------------------------------------------------------------------- Bioinformatics Department BioVisioN AG, Hannover

Hi All, while looking why the cclust(cclust) doesn't work for 1-dimensional data, I've found unpleasant behavior in semantics of R. Indeed: is.matrix(matrix(cbind(c(1,2,3,4)),ncol=2)[1:2,]) == TRUE but: is.matrix(matrix(c(1,2))[1:2,]) == FALSE kind regards, Valery A.Khamenya --------------------------------------------------------------------------- Bioinformatics

Dear Christian, first of all thank you for your answer. I am going to parse through the pages you told me. Meanwhile I'd like to note that probably it is a good idea to put 2-3 lines of R-code demonstrating such a simple needs somnewhere in docs of `cluster' package. E.g. x<-rnorm(500) ... # output means we have rather 1 claster x<-c(rnorm(500), rnorm(500)+5)

> See the 'Writing R Extensions' manual, specifically > Creating R Packages -> Writing package vignettes thank you, i saw this entry. However, this entry is rather about how to include documents (in particular Sweave-based) into a package. But I have meant smth else. Let me explain in example. Today I use emacs as environment for my R-sessions. I am quite happy to use

Hi devels, i did not find at this page: http://developer.r-project.org/ideas.txt any ideas concerning incorporating documentation possibilities (say, Sweave-based) into R-scripts. Was it discussed already? (If discussed, then what is the decision/conclusion then?) thanks, Valery

Hi all, Situation: there is a function `f' already defined by someone and provided in package. `f' looks like that: f <- function() { x+1 } i.e. `f' is not closed i.r.t. term `x' now I have my own function `g', where I'd like to override variable `x' while calling `f': x <- "dummy gloabal value" g <- function() { x

Hi all, I took a look at last 2 months post in R-help maillist and surfed through the R-project.org . Unfortunately, I can't find some page with roadmap/statements about major changes coming in R-2.0 in comparison to R-1.9 Could anyone point me to the right URL? Thank you in advance. -- Valery

Hi all, I took a look at last 2 months post in R-help maillist and surfed through the R-project.org . Unfortunately, I can't find some page with roadmap/statements about major changes coming in R-2.0 in comparison to R-1.9 Could anyone point me to the right URL? Thank you in advance. -- Valery

Hi all, What is the right portable way to save graphics in batch mode? Remarks: 1. Problem is STFWed and RTFMed. In particular a short note about png() is found in R-FAQ. In fact, there were stated that png() is not reliable under Linux in batch mode. 2. savePlot under windows is quite convenient, but not supplied under Linux. 3. pdf() + postscript() < savePlot()

> Nothing to do with me: you should report problems with > packages to the > maintainers, rather than R-help or a member of R-core. OK. I've sent a note about cclust patch to Evgenia Dimitriadou Thank you for your valueable comments. (No more reply needed in this thread) kind regards, Valery A.Khamenya ---------------------------------------------------------------------------

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

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,