similar to: Numerical Integration in 1D

Dear all, I would be very grateful if you could help me with: Given the regularized gamma function Reg=int_0^r (x^(k-1)e^(-x))dx/int_0^Inf (x^(k-1)e^(-x))dx ; 0<r<Inf (which is eventually the ratio of the Incomplete gamma function by the gamma function), does anyone know of a package in R that would evaluate the derivative of the inverse of Reg with respect to k? I am aware that the

Hey fellas: I would like to integrate the following function: integrand <- function (x,t) { exp(-2*t)*(2*t)^x/(10*factorial(x)) } with respect to the t variable, from 0 to 10. The variable x here works as a parameter: I would like to integrate the said function for each value of x in 0,1,..,44. I have tried Vectorize to no avail. Thanks in advance, jose romero

I'm trying to obtain numerical derivative of a probability computed with mvtnorm with respect to its parameters using grad() and jacobian() from NumDeriv. To simplify the matter, here is an example: PP1 <- function(p){ thetac <- p thetae <- 0.323340333 thetab <- -0.280970036 thetao <- 0.770768082 ssigma <- diag(4) ssigma[1,2] <- 0.229502120

Does anybody know of a function that implements the derivative (gradient) of the multivariate normal density with respect to the *parameters*? It?s easy enough to implement myself, but I?d like to avoid reinventing the wheel (with some bugs) if possible. Here?s a simple example of the result I?d like, using numerical differentiation: library(mvtnorm) library(numDeriv) f=function(pars, xx, yy)

Hi all, I have some wind data (U and V components) and I would like to compute Vorticity and Divergence of these fields. Is there any R function that can easily do that? Thanks in advance for any help Igor Oliveira CSAG, Dept. Environmental & Geographical Science, University of Cape Town, Private Bag X3, Rondebosch 7701. Tel.: +27 (0)21 650 5774 South Africa Fax: +27 (0)21

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

I fit my CDF to sum of exponentials and now I want to take the numerical derivative of this function to obtain probability density.I will really appreciate your help reagrding the error messages I am getting which I don't understand. * * > fitterma <- function(xtime) { a <- -0.09144115 b <- -0.01335756 c <- -2.368057 d <- -0.00600052

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

Quick question: Which function do you use to calculate partial derivatives from a model equation? I've looked at deriv(), but think it gives derivatives, not partial derivatives. Of course my equation isn't this simple, but as an example, I'm looking for something that let's you control whether it's a partial or not, such as: somefunction(y~a+bx, with respect to x,

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 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 R-users,   I have this code below and I understand the error message but do not know how to correct it.  My question is how do I get rid of “with absolute error < 7.5e-06” attach to value of cdf so that I can carry out the calculation.   integrand <- function(z) { alp  <- 2.0165   rho  <- 0.868   # simplified expressions   a      <- alp-0.5   c1     <-

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

Dear R users, I am trying to find the mle that involves integration. I am using the following code and get an error when I use the nlm function d<-matrix(c(1,1,0,0,0,0,0,0,2,1,0,0,1,1,0,1,2,2,1,0),nrow=10,ncol=2) h<-matrix(runif(20,0,1),10) integ<-matrix(c(0),nrow=10, ncol=2) ll<-function(p){ for (k in 1:2){ for(s in 1:10){ integrand<-function(x)

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)

Hi, my name is Marcel R. Lopes. My problem is, I made a code to calculate the estimates of a Cox model with random effects. Used to optimize the R command for this. The estimates were calculated correctly, but the Hessian matrix does not have good values. The same thing was done in SAS and gave good results for the Hessian Matrix. Where is the problem in R? As the Hessian is calculated?. How

Dear R users When I use OPTIM with BFGS, I've got a significant result without an error message. However, when I use OPTIMX with BFGS( or spg), I've got the following an error message. ---------------------------------------------------------------------------------------------------- > optimx(par=theta0, fn=obj.fy, gr=gr.fy, method="BFGS", >

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

Dear all R users, Is there any way to calculate hessian matrix of a given function at any given point? Regards [[alternative HTML version deleted]]