similar to: Problem following an R bug fix to integrate()

Hi, I'm trying to compile two functions into one function. the first funtion is called 'fs' which is self-made function, another function is from the built-in 'integration' function that is copy-paste-edited. If built separatey, these functions work well. However that is not the case if combines together, where certainly I made mistake somewhere when constructing the code.

> version _ platform i686-pc-linux-gnu arch i686 os linux-gnu system i686, linux-gnu status major 1 minor 7.1 year 2003 month 06 day 16 language R Bug: integrate(f,lower,upper,extra_args) where f <- function(x,extra_args) { body } integrate doesn't pass the extra arguments when calling f. As a first check of this finding I integrated dnorm from

Hi, I noticed a minor flaw in integrate() from package stats: Taking up arguments lower and upper from integrate(), if (lower == Inf) && (upper == Inf) or if (lower == -Inf) && (upper == -Inf) integrate() calculates the value for (lower==-Inf) && (upper==Inf). Rather, it should return 0. Quick fix: ### old code ### ### [snip] else {

Hi everyone, ? I am trying to get a point of intersection between a polyline and a straight line ?.. and get the x and y coordinates of this point. For exemplification consider this: ? ? set.seed(123) ? k1 <-rnorm(100, mean=1.77, sd=3.33) ?k1 <- sort(k1) q1 <- rnorm(100, mean=2.37, sd=0.74) q1 <- sort(q1, decreasing = TRUE) plot(k1, q1, xlim <- c((min(k1)-5),

Dear @ll. I have to calculate numerical integrals for triangular and trapezoidal figures. I know you can calculate the exactly, but I want to do it this way to learn how to proceed with more complicated shapes. The code I'm using is the following: integrand<-function(x) { print(x) if(x<fx[1]) return(0) if(x>=fx[1] && x<fx[2]) return((x-fx[1])/(fx[2]-fx[1]))

Dear all, This is the first time I am posting to the r-devel list. On StackOverflow, they suggested that the strange behaviour of integrate() was more bug-like. I am providing a short version of the question (full one with plots: https://stackoverflow.com/q/55639401). Suppose one wants integrate a function that is just a product of two density functions (like gamma). The support of the

Hello, fellow Rdicts, I have the code for the program below. I need to integrate a function of "x" and "p". I use integrate to integrate over "x" and pass "p" as an additional argument. "p" is specified and given default value in the argument list. Still, integrate() cannot read "p", unless I explicitly insert a numeric value in the

Dear all, I have some issues with integrate in R thus I would like to request your help. I am trying to calculate the integral of f(x)*g(x). The f(x) is a step function while g(x) is a polynomial. If f(x) (step function) changes its value only few times (5 or 6 'steps') everything is calulated ok(verified results in scrap paper) but if f(x) takes like 800 different values I receive the

Dear list, [cross-posting from Stack Overflow where this question has remained unanswered for two weeks] I'd like to perform a numerical integration in one dimension, I = int_a^b f(x) dx where the integrand f: x in IR -> f(x) in IR^p is vector-valued. integrate() only allows scalar integrands, thus I would need to call it many (p=200 typically) times, which sounds suboptimal. The

Hi all, Here is an integration function require(pracma) # for 'quadinf' myint=function(j) { quadinf(function(x) (1/(1+exp(-x)))^j*(1-1/(1+exp(-x)))^(k-j)*dnorm(x,mu,casigma),-Inf,Inf) } in any optimization routine. It works fine most of the time but failed with some particular sets of values, say one of the following: k=20 mu=-1.978295 casigma=0.008326927 >

Hello, We are trying to use R to simulate a model based on parameters 'a' and 'b'. This involves the following integration: model<-function(s,x,a,b)(exp(-s*x*10^-5.5)*(s^(a-1)*(1-s)^(b-1))) g<- function(x,a,b){ out<-c() for (i in 1:length(x)){ out[i]<-1- (integrate(model,0,1,x[i],a,b)$value / beta(a,b)) } out } x<-

Hi , R is a new language for me so sorry in advance if this error is to basic for posting. I have tried the R manual and search online for quite a few, if anyone could help i would be very thankful. Here is my code. kappa = 1.1 theta = 0.1 sigma = 0.4 rho = -0.6 v0 = 0.2 r = 0.05 T = 0.5 s0 = 1 K = 0.5 type = 1 Hestoncall = function(kappa,theta,sigma,rho,v0,r,T,s0,K,type) { u = 0.5 b

I am fairly new to R. I find it surprising that f <- function(x,a) {x-a} uniroot(f, c(0,1), a=.5) works, but integrate(f, 0, 1, a=.5) gives an error: Error in integrate(f, 0, 1, a = 0.5) : argument 4 matches multiple formal arguments What is the best way of avoiding such surprises? Is there a way of telling integrate() that the 'a' argument is for f()? If I wrote my own function

Hello, I've a question concerning the display of interval data. A sample dataset where X is an interval between Xa and Xb which should be displayed: Y=c(15,14,23,18,19,9,19,13) Xa=c(17,22,21,18,19,25,8,19) Xb=c(22,22,29,34,19,26,17,22) X = (Xa+Xb)/2 It's easily possible to plot the mean of the interval like: plot(X,Y) afterwards I can create lines for the interval with:

I have a question concerning the new Windows toolchain for R >= 2.14.2. When trying out my package 'pracma' on the win-builder development version it will stop with the following error message: > f3 <- function(x, y) sqrt((1 - (x^2 + y^2)) * (x^2 + y^2 <= 1)) > dblquad(f3, -1, 1, -1, 1) # 2.094395124 , i.e. 2/3*pi , err = 2e-8 Warning in sqrt((1 - (x^2 + y^2)) *

Dear all, I have a function to optimize for a set of parameters and want to set a constraint on only one parameter. Here is my function. What I want to do is estimate the parameters of a bivariate normal distribution where the correlation has to be between -1 and 1. Would you please advise how to revise it? ex=function(s,prob,theta1,theta,xa,xb,xc,xd,t,delta) { expo1=

Dear all Is there a simpler method to achieve the following: When I obtain an empty data.frame after subsetting, I need for it to contain one line of NAs. Here's a dummy example: > (.xb <- iris[ iris$Species=='zz', ]) [1] Sepal.Length Sepal.Width Petal.Length Petal.Width Species <0 rows> (or 0-length row.names) > dim(.xb) [1] 0 5 > (.xa <-

I have two lists: xa <- list( X=c(1,2,3), Y=c(4,5,6), Z=c(7,8,9) ) xb <- with( barley, tapply( X=seq(1:nrow(barley)), INDEX=site , FUN=function(z)yield[z])) I can convert xa to a dataframe easily with: as.data.frame(xa) But if i try the same with xb I get: as.data.frame(xb) Error in as.data.frame.default(xb) : can't coerce array into a data.frame What

Hi, I am writing a function to plot a pdf of a distribution, GNL.pdf.fn = function(x,mu,sigma,alpha,beta,rho) { y = x-rho*mu cf.fn = function(s){ cplex = complex(1,0,1) temp1 = alpha*beta*exp(-sigma*s^2/2) temp2 = (alpha-cplex*s)*(beta+cplex*s) out = (temp1/temp2)^rho out } temp.fn = function(s){ (Mod(cf.fn(s)))*cos(Arg(cf.fn(s))-s*y) } int.fn =

Rembert.DeBlander@econ.kuleuven.ac.be wrote: >>version > PLEASE: a) Use a sensible subject line b) Please post only post bug reports if you are sure it is a bug (and here it is not a bug!) c) Check the recent R version (1.9.1) if posting bugs, not an outdated one! d) Only named arguments are passed through the ... argument: integrate(dnorm, lower=-Inf, upper=3, mean=-1, sd=7) Uwe