similar to: performance of adaptIntegrate vs. integrate

Hello, I am trying to use adaptIntegrate function but I need to pass on a few additional parameters to the integrand. However, this function seems not to have the flexibility of passing on such additional parameters. Am I missing something or this is a known limitation. Is there a good alternative to such restrictions, if there at all are? Many thanks for your time. HC -- View this message in

Hi all, it seems that there is problem with function "adaptIntegrate", when the integration limits is infinity. Please see the code below. The second integration does not seem to work. Can anyone familiar with this give some help? Thank you with much. Hanna library(mnormt) library(cubature) ff <- function(x, rho){ mu <- rep(0,3) Sigma

Hi, I am using adaptIntegrate from Cubature to do numerical integration on a double integral with a 1 x 2 vector x. Say the function is something simple to start like f(x)=x1*x2 and I wish to integrate x1 over (0,365-x2) and x2 over (0,365) f <- function(x) {(x[2])*(x[1])} # "x" is vector int1<-adaptIntegrate(f, lowerLimit = c(0, 0), upperLimit = c(365-x[2], 365)) I recieve

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

Hi R-users. I'm having difficulty with an integration in R via the package "cubature". I'm putting it with a simple example here. I wish to integrate a function like: f(x1,x2)=2/3*(x1+x2) in the interval 0<x1<x2<7. To be sure I tried it by hand and got 114.33, but the following R code is giving me 102.6667.

Hi everyone, I have been using adaptIntegrate from the cubature package for a multidimensional integral that has infinite variance (and so not appropriate for Monte Carlo techniques). Most of the time it works but sometimes (though not always) when I slightly increase the accuracy I want, or increase the bounds of integration I get the following error: REAL() can only be applied to a

Dear R-users, I am facing problem with integrating in R a likelihood function which is a function of four parameters. It's giving me the result at the end but taking more than half an hour to run. I'm wondering is there any other efficient way deal with. The following is my code. I am ready to provide any other description of my function if you need to move forward.

I want to measure the error in the estimation of a 2 dimensional density function that is calculated using an integral but run into problems trying to integrate with adaptIntegrate because the integrand also calls the function adaptIntegrate. In particular I want \int \hat{f}(x,y) - f(x,y) dx dy where \hat{f}(x,y) = \int K(a,b, x, y) da db and in this simulation study I know what the true value

Hi All, I get the message failed with message ‘Dimension out of range’ when using cuhre in package R2Cuba. Does anyone know what this mean? Or would I need to email the package author? The funny thing is it does give a result and comparing it to "adaptIntegrate" in package cubature, the two numbers are very close. Thanks, Sachin [[alternative HTML version deleted]]

Dear all, I got an error message when running the following code. Can anyone give any suggestions on fixing this type of error? Thank you very much in advance. Hanna > integrand <- function(x, rho, a, b, z){ + x1 <- x[1] + x2 <- x[2] + Sigma <- matrix(c(1, rho, rho, 1), 2,2) + mu <- rep(0,2) + f <-

Dear R users, In the code below, I am trying to print the result of my loop function. The output first gives me the result for k=1, and then for k=1 and k=2. I only want the last output which is [,1] [,2] [1,] 0.1700065 0.5002659 [2,] 0.3080273 0.4954731 [3,] 0.4844886 0.4544306 [4,] 0.5062987 0.1868154 [5,] 0.5846982 0.4353522 [6,] 0.4332621 0.2202922 [7,] 0.4391985

Dear R-users, I'm wondering how to calculate this double integral in R: int_a^b int_c^y g(x, y) dx dy where g(x,y) = exp(- alpha (y - x)) * b Thanks for answering! Cheers, Alui [[alternative HTML version deleted]]

Hello: The example "integrate(dnorm,0,20000)" says it "fails on many systems". I just got 0 from it, when I should have gotten either an error or something close to 0.5. I got this with R 2.12.0 under both Windows Vista_x64 and Linux (Fedora 13); see the results from Windows below. I thought you might want to know. Thanks for all your work in creating

hello I work on the probabilities of bivariate normal distribution. I need integrate  the following function. f (x, y) = exp [- (x ^ 2 + y ^ 2 + x * y)] with - ∞ ≤ x ≤ 7.44 and - ∞ ≤ y ≤ 1.44   , either software R or  matlab Version R 2009a Thank you for helping me Regards Mezouara hicham PhD in Metrology Hicham_dess @ yahoo.fr [[alternative HTML version deleted]]

Hello Dear List members, as you can see (and guess) from the code below adaptIntegrate(f,lowerLimit=c(-1,-1),upperLimit=c(.9999,.9999)) $integral [1] 9.997e-09 $error [1] 1.665168e-16 $functionEvaluations [1] 17 $returnCode [1] 0 > adaptIntegrate(f,lowerLimit=c(-1,-1),upperLimit=c(1,1)) the last command runs for 45 mins now. -this one takes only less than sec:

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

Dear R helpers I am working on the Bi-variate Normal distribution probabilities. I need to double integrate the following function (actually simplified form of bivariate normal distribution) f(x, y) = exp [ - 0.549451 * (x^2 + y^2 - 0.6 * x * y) ] where 2.696 < x < 3.54 and -1.51 < y < 1.98 I need to solve something like INTEGRATE (2.696 to 3.54) dx INTEGRATE [(-1.51 to 1.98)]

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

Hi folks, I am having a question about efficiently finding the integrals of a list of functions. To be specific, here is a simple example showing my question. Suppose we have a function f defined by f<-function(x,y,z) c(x,y^2,z^3) Thus, f is actually corresponding to three uni-dimensional functions f_1(x)=x, f_2(y)=y^2 and f_3(z)=z^3. What I am looking for are the integrals of these three

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