similar to: vectorized uni-root?

In looking at rootfinding for the histoRicalg project (see gitlab.com/nashjc/histoRicalg), I thought I would check how uniroot() solves some problems. The following short example ff <- function(x){ exp(0.5*x) - 2 } ff(2) ff(1) uniroot(ff, 0, 10) uniroot(ff, c(0, 10), trace=1) uniroot(ff, c(0, 10), trace=TRUE) shows that the trace parameter, as described in the Rd file, does not seem to be

Hi, I am new to R, and as a first exercise, I decided to try to implement an XIRR function using the secant method. I did a quick search and saw another posting that used the Bisection method but wanted to see if it was possible using the secant method. I would input a Cash Flow and Date vector as well as an initial guess. I hardcoded today's initial date so I could do checks in Excel.

Despite my years with R, I didn't know about trace(). Thanks. However, my decades in the minimization and root finding game make me like having a trace that gives some info on the operation, the argument and the current function value. I've usually found glitches are a result of things like >= rather than > in tests etc., and knowing what was done is the quickest way to get there.

curiosity---given that vector operations are so much faster than scalar operations, would it make sense to make uniroot vectorized? if I read the uniroot docs correctly, uniroot() calls an external C routine which seems to be a scalar function. that must be slow. I am thinking a vectorized version would be useful for an example such as of <- function(x,a) ( log(x)+x+a ) uniroot( of, c(

Dear Prof Azzalini, You have an interesting example of recursive use of uniroot(). [re-cited at the end] However, note that R currently has the same problem as S-plus: Uniroot() doesn't work reliably, recursively. When you found it to be better, you were just lucky. The relevant file in R's source, src/main/optimize.c says /* WARNING : As things stand, these routines should

I have problems reading a file with more than one row to carry out mathematical calculations I have a a file of the form mu1 mu2 alpha beta Wsigma sigmaA b r 25 15 .05 .05 22 3 .3 .5 30 20 .1 .2 22 .3 .3 .5 I intend to read one row , carry out the calculations and then the next row with which I intend to do the same calculations. I do the following.

dear R experts--- I am experimenting with multicore processing, so far with pretty disappointing results. Here is my simple example: A <- 100000 randvalues <- abs(rnorm(A)) minfn <- function( x, i ) { log(abs(x))+x^3+i/A+randvalues[i] } ?## an arbitrary function ARGV <- commandArgs(trailingOnly=TRUE) if (ARGV[1] == "do-onecore") { ?library(foreach) ?discard <-

Hi all, This is probably a blindingly obvious question: Why does it matter in the uniroot function whether the f() values at the end points that you supply are of the same sign? For example: f <- function(x,y) {y-x^2+1} #this gives a warning uniroot(f,interval=c(-5,5),y=0) Error in uniroot(f, interval=c(-5, 5), y = 0) : f() values at end points not of opposite sign #this doesn't give a

I tend to avoid the the trace/verbose arguments for the various root finders and optimizers and instead use the trace function or otherwise modify the function handed to the operator. You can print or plot the arguments or save them. E.g., > trace(ff, print=FALSE, quote(cat("x=", deparse(x), "\n", sep=""))) [1] "ff" > ff0 <- uniroot(ff, c(0, 10))

R-Helpers: I would like to perform sample size calculations for an experiment. As part of this process, I would like to know how various assumptions affect the sample size calculation. For instance, one thing that I would like to know is how the calculated sample size changes as I vary the difference that I would like to detect. I tried the following first, but got the associated error

hi: could someone please point me to a function that allows me to solve general non-linear functions? > irr.in <- function(r, c1, c2, c3 ) { return(c1+c2/(1+r) + c3/(1+r)^2); } > solve.nonlinear( irr.in, -100, 60, 70 ); 0.189 If someone has written an irr function, this would be helpful, too---though not difficult to write, either. thanks for any pointers. Regards, /iaw

Dear fellow R-users, Is there a function that does the bisection method? I was unable to find one. Thanks in advance. Gregory [[alternative HTML version deleted]]

I have the following function for which I need to find the root of a: f <- function(R,a,c,q) sum((1 - (1-R)^a)^(1/a)) - c * q To give context for the problem, this is a psychometric issue where R is a vector denoting the percentage of students scoring correct on test item i in class j, c is the proportion correct on the test by student k, and q is the number of items on the test in total. I

Hi all, I am writing a simple function to implement regularfalsi (secant) method. ################################################### regulafalsi=function(f,x0,x1){ x=c() x[1]=x1 i=1 while ( f(x[i])!=0 ) { i=i+1 if (i==2) { x[2]=x[1]-f(x[1])*(x[1]-x0)/(f(x[1])-f(x0)) } else { x[i]=x[i-1]-f(x[i-1])*(x[i-1]-x[i-2])/(f(x[i-1])-f(x[i-2])) } } x[i] }

dear R experts: I want to define a function the calculates the black-scholes value. it takes 5 named parameters, BS <- function(S,K,dt,rf,sigma) {} . let's presume I want to be able to call this not only with my 5 numeric vectors BS( sigma=0.3, S=100, K=100, dt=1, rf=0.1 ) and BS( 100, 100, 1, 0.1, 0.3), but also with a data frame that contains the variables alll in a neat data frame

SAS has DUD (Does not Use Derivatives)/Secant Method for nonlinear regression, does R offer this option for nonlinear regression? I have read the helpfile for nls() and could not find such option, any suggestion? Thanks, Derek [[alternative HTML version deleted]]

Hi R-help! I'm trying to understand how R's nlm function updates its estimate of the Hessian matrix. The Dennis/Schnabel book cited in the references presents a number of different ways to do this, and seems to conclude that the positive-definite secant method (BFGS) works best in practice (p201). However, when I run my code through the optim function with the method as "BFGS",

Hi, I replaced my Rtools today as posted at http://www.murdoch-sutherland.com/Rtools/Rtools.exe Trying to build R-devel_2007-12-13.tar.gz without modifying MkRules gives the gfortran command not found error below. I am wondering if gfortran.exe is missing from (recent?) Rtools.exe or I am doing something wrong. Thanks to hints at Duncan's site, I worked around the error by adding

hello, please can anyone help me out. Am a new user of R program. Am having problem with this code below, not getting the expected results. 1. Each m, the cumulative sum should be 1.000 but the 2nd and 3rd m returned 2.000 and 3.000 instead of 1.000. 2. to get the LCL(m) and UCL(m) for each m base on these instructions if out.cum > 0.025 then LCL(m)= y-1 if out.cum >0.975

Colleagues, I am trying to learn to use uniroot to solve a simple linear equation. I define the function, prove the function and a call to the function works. When I try to use uniroot to solve the equation I get an error message, Error in yfu n(x,10,20) : object 'x' not found. I hope someone can tell we how I can fix the problem