similar to: how to pass a function to a function inside a function

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 {

> 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

I have been told by the CRAN administrators that the following code generated an error on 64-bit Fedora Linux (gcc, clang) and on Solaris machines (sparc, x86), but runs well on all other systems): > fn <- function(x, y) ifelse(x^2 + y^2 <= 1, 1 - x^2 - y^2, 0) > tol <- 1.5e-8 > fy <- function(x) integrate(function(y) fn(x, y), 0, 1,

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]))

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 c) Check the recent R version (1.9.1) if posting bugs, not an outdated one!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

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

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

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

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

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, 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 =

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

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

Hi! I was wondering if there are any other functions for numerical integration, besides 'integrate' from the stats package, but which wouldn't require the integrand to be vectorized. Oh, and must be capable of integrating over (-inf,+inf). Thanks in advance, Eduardo Horta [[alternative HTML version deleted]]

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 >

Dear R users, i would like to transform the following function from R-code to C-code and call it from R in order to speed up the computation because in my other functions this function is called many times. `dgcpois` <- function(z, lambda1, lambda2) { `f1` <- function(alpha, lambda1, lambda2) return(exp(log(lambda1) * (alpha - 1) - lambda2 * lgamma(alpha))) `f2` <-

I've only been using R on and off for 9 months and started using the glasso package for sparse covariance estimation. I know the concept is to shrink some of the elements of the covariance matrix to zero. However, say I have a dataset that I know has some underlying "baseline" covariance/correlation (say, a value of 0.3), how can I change or incorporate that into to the

Hello everybody. I would like to pose a question regarding a warning message after running a function of my own. The function I created for computing the p-value of the dw statistic has a command line like this: »dwf0 <- function(dw,eigen) { carfun <- function(x) { (prod(1+2*(eigen-dw)*1i*x)^(-1/2)-prod(1-2*(eigen-dw)*1i*x)^(-1/2))/(1i*x) } ; 1/2+integrate(f=carfun,lower = 0,upper =

Hi i am having a problem with the 'integrate' function the function i want to integrate has the form sum(vector^x) i have defined the function with a for loop first - integrandtotest <- function(x) {a<-rep(0,len=2) for (i in 1:2) {a[i]<-t[i]^x} sum(a) } the results gives errors ########### Error in integrate(integrandtotest, lower = 0.1, upper =

Hello, Rlisters I have to compute p-values that are on the tail of the distribution, P-values < 10^-20. However, my current implementations enable one to estimate P-values up to 10^-12, or so. A typical example is found below, where t is my critical value. ########### example - code adapted from Rassoc ####################### rho01 = 0.5 rho105 = 0.5 rho005 = 0.5 t = 8 z = 2