similar to: numerical integration and 'non-finite function value' error

Dear list, I'm seeking some advice regarding a particular numerical integration I wish to perform. The integrand f takes two real arguments x and y and returns a vector of constant length N. The range of integration is [0, infty) for x and [a,b] (finite) for y. Since the integrand has values in R^N I did not find a built-in function to perform numerical quadrature, so I wrote my own after

Dear R users, When I run the code below, I get the error "Error in integrate(integrand, 0, Inf) : non-finite function value". The code works if the function returns only "sum(integ)". However, I want to add "cmh" to it. When I add "cmh" I get that error. I can't figure out why this is happening because my integrate function has nothing to do with

Hi R users, I have a couple of questions about some problems that I am facing with regard to numerical integration and optimization of likelihood functions. Let me provide a little background information: I am trying to do maximum likelihood estimation of an econometric model that I have developed recently. I estimate the parameters of the model using the monthly US unemployment rate series

Dear All, I need to perform a numerical integration of one dimensional fucntions. The extrems of integration are both finite and the functions I'm working on are quite complicated. I have already tried both area() and integrate(), but they do not perform well: area() is very slow and integrate() does not converge. Are in R other functions for numerical integration of one dimentional

Hi there I'm trying to construct a model of mortality risk in 2D space that requires numerical integration of a hazard function, for which I'm using the integrate function. I'm occasionally encountering parameter combinations that cause integrate to terminate with error "Error in integrate... the integral is probably divergent", which I'm not sure how to interpret. The

I need to calcuate the cumulative probability for the Natural Exponential Family - Hyperbolic secant distribution with a parameter theta between -pi/2 and pi/2. The integration should be between 0 and 1 as it is a probability. The function "integrate" works fine when the absolute value of theta is not too large. That is, the NEF-HS distribution is not too skewed. However, once the

In the help for ?integrate: >When integrating over infinite intervals do so explicitly, rather than just using a large number as the endpoint. This increases the chance of a correct answer ? any function whose integral over an infinite interval is finite must be near zero for most of that interval. I understand that and there are examples such as: ## a slowly-convergent integral integrand

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 UseRs, I'm curious about the derivative of n!. We know that Gamma(n+1)=n! So when on takes the derivative of Gamma(n+1) we get Int(ln(x)*exp(-x)*x^n,x=0..Inf). I've tried code like > integrand<-function(x) {log(x)*exp(x)*x^n} > integrate(integrand,lower=0,upper=Inf) It seems that R doesn't like to integrate for any n, and I was wondering if anyone knew a way around

Hello, I am a novice R user and am having difficulty retrieving the values from 21 iterations of the R function integrate. The only way I have found is to do a write.table and then a read.table as shown in the code below. I would rather capture the 21 values inside the braces ( sapply might work, but I can't set it up without getting an error in function) so I could compute the

Greetings, Sorry, the last message was sent by mistake! Here it is again: I encounter a strange problem computing some numerical integrals on [0,oo). Define $$ M_j(x)=exp(-jax) $$ where $a=0.08$. We want to compute the $L^2([0,\infty))$-inner products $$ A_{ij}:=(M_i,M_j)=\int_0^\infty M_i(x)M_j(x)dx $$ Analytically we have $$ A_{ij}=1/(a(i+j)). $$ In the code below we compute the matrix

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, Am not sure if my code itself is correct. Here's what am trying to do: Minimize integration of a function of gaussian distributed variable 'x' over the interval qnorm(0.999) to Inf by changing value of parameter 'mu'. mu is the shift in mean of 'x'. Code: # x follows gaussian distribution # fx2 to be minimized by changing values of mu # integration to be done over

I am a novice user of "R" and I'm learning with R version 2.8.1, using WinEdt_1.8.1, under Widows Vista Home Version. ## The test function below, from a vector input, returns vector values: # and it contains an "ifelse"statement TEST<- function(x) { low<- -x^2 up<- x^4 ifelse(x>=0,up,low ) } u<- seq(-1,1,0.5) TEST(u)

Dear all, I am a new user to R and I am using pracma and nloptr libraries to minimize a numerical integration subject to a single constraint . The integrand itself is somehow a complicated function of x and y that is computed through several steps. i formulated the integrand in a separate function called f which is a function of x &y. I want to find the optimal value of x such that the

Dear List-Members, since 3 weeks I have been heavily working on reproducing the results of an economic paper. The method there uses the numerical solution of an integral within nonlinear least squares. Within the integrand there is also some parameter to estimate. Is that in the end possible to implement in R [Originally it was done in GAUSS]? I'm nearly into giving up. I constucted an

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.

Dear expeRts, I somehow don't see why the following does not work: integrand <- function(x, vec, mat, val) 1 # dummy return value A <- matrix(runif(16), ncol = 4) u <- c(0.4, 0.1, 0.2, 0.3) integrand(0.3, u, A, 4) integrate(integrand, lower = 0, upper = 1, vec = u, mat = A, val = 4) I would like to integrate a function ("integrand") which gets an "x" value (the

Dear All, Can R perform multivariate integration with infinite limits of integration? Thanks in advance, Paul

Full_Name: José Enrique Chacón Version: 1.5.0 and 1.3.1 OS: Windows Millenium Submission from: (NULL) (158.49.28.155) Dear reader: I was trying to evaluate the L2 error produced when estimating the density function N(0,1) from a sample of size 100 using a kernel density estimate. It produced a strange value. You can reproduce the process by typing samp<-rnorm(100)