similar to: Numerical Derivatives in R

Hi, I have been trying to do numerical differentiation using R. I found some old S code using Richardson Extrapolation which I managed to get to work. I am posting it here in case anyone needs it. ######################################################################## richardson.grad <- function(func, x, d=0.01, eps=1e-4, r=6, show=F){ # This function calculates a numerical approximation

Ah... I searched for half an hour for this function... you know, the help function in R could really be a lot better... But wait a minute... looking at this, it appears you have to pass in an expression. What if it is an unknown function, where you only have a handle to the function, but you cannot see it's implementation ? Will this work then ? -----Original Message----- From: Berton Gunter

Hi there, I have a function which has a variable called show as an input: richardson.grad <- function(func, x, d=0.01, eps=1e-4, r=6, show=F){ # do some things if(show) { cat("\n","first order approximations", "\n") print(a.mtr, 12) } #do more things and return } The show variable is being used as a flag to show intermediate

Hi, Is there a way to send an ESC command to the console from within a script window, without using the mouse ? Thanks, Tolga

Is there a package in R which implements numerically solves pde ? Thanks, Tolga

Dear R Users, Anyone know of a version of Rbbg compiled for R 2.15.2 . The current version does not appear to work with 2.15.2 > install.packages("Rbbg", repos = "http://r.findata.org") Installing package(s) into ?C:/Users/t_uzu_000/Documents/R/win-library/2.15? (as ?lib? is unspecified) Warning: unable to access index for repository http://r.findata.org/src/contrib

Dear R Users, Does anyone know of a package which can generate random realisations of a double-exponential jump diffusion process with a drift ? Something where I can specify the likelihoods of an up or a down jump, the drift rate, and the mean size, and get back a vector of realisation of the process (for purposes of a Monte-Carlo). Kind regards, Tolga

Hi there, Is there an implementation of the Gaveh Stehfest algorithm in R somewhere ? Or some other inversion ? Thanks, Tolga

Hi, Having a weird problem with the integrate function. I have a function which calculates a loss density: I'd like to integrate it to get the distribution. The loss density function is: lossdensity<-function(p,Beta,R=0.4){ # the second derivative of the PDF # p is the default probability of the pool at which we are evaluating the lossdensity # Beta is the correlation with the market

# Newbie alert # I am wanting to multiply the rows in a dataframe by a vector. # However, the default behavior appears to be for the vector to be applied # column wise. For example: vct <- 1:4 df <- data.frame(c1 = 5:10, c2= 6:11, c3=7:12, c4=8:13) multTheTwo <- vct * df multTheTwo # This results in the vector getting cycled columnwise # c1 c2 c3 c4 # 1 5 18 7 24 # 2 12 28 16 36 # 3

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

Hi all, I was trying to rebuild mtr (http://vault.centos.org/6.7/os/Source/SPackages/mtr-0.75-5.el6.src.rpm) and I keep getting: ==== Executing(%install): /bin/sh -e /var/tmp/rpm-tmp.gu9Ds0 + umask 022 + cd /root/rpmbuild/BUILD + '[' /root/rpmbuild/BUILDROOT/mtr-0.75-5.el6.x86_64 '!=' / ']' + rm -rf /root/rpmbuild/BUILDROOT/mtr-0.75-5.el6.x86_64 ++ dirname

On 8 March 2016 at 16:15, Digimer <lists at alteeve.ca> wrote: > On 08/03/16 07:11 AM, James Hogarth wrote: > > On 8 March 2016 at 10:07, Leon Fauster <leonfauster at googlemail.com> > wrote: > > > >> Am 08.03.2016 um 01:50 schrieb Digimer <lists at alteeve.ca>: > >>> I'm not surprised, given that it is in the repo. That's why I was

Hi all. I have a numerical function f(x), with x being a vector of generic size (say k=4), and I wanna take the numerically computed gradient, using deriv or numericDeriv (or something else). My difficulties here are that in deriv and numericDeric the function is passed as an expression, and one have to pass the list of variables involved as a char vector... So, it's a pure R programming

On 8 March 2016 at 17:22, Digimer <lists at alteeve.ca> wrote: > On 08/03/16 11:36 AM, James Hogarth wrote: > > On 8 March 2016 at 16:15, Digimer <lists at alteeve.ca> wrote: > > > >> On 08/03/16 07:11 AM, James Hogarth wrote: > >>> On 8 March 2016 at 10:07, Leon Fauster <leonfauster at googlemail.com> > >> wrote: > >>>

On 8 March 2016 at 19:02, Digimer <lists at alteeve.ca> wrote: > On 08/03/16 01:51 PM, James Hogarth wrote: > > On 8 March 2016 at 17:22, Digimer <lists at alteeve.ca> wrote: > > > >> On 08/03/16 11:36 AM, James Hogarth wrote: > >>> On 8 March 2016 at 16:15, Digimer <lists at alteeve.ca> wrote: > >>> > >>>> On

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

On 8 March 2016 at 10:07, Leon Fauster <leonfauster at googlemail.com> wrote: > Am 08.03.2016 um 01:50 schrieb Digimer <lists at alteeve.ca>: > > I'm not surprised, given that it is in the repo. That's why I was asking > > if anyone tried building it themselves and, if so, did they have the > > same issue as I describe below? > > > >

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,

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