similar to: Taking Integral and Optimization using Integrate, Optim and maxNR

Hi R-users, Recently, I use maxNR function to find maximizer. I have error appears as follows Error in maxNRCompute(fn = fn, grad = grad, hess = hess, start = start, : NA in the initial gradient My code is mu=2 s=1 n=300 library(maxLik) set.seed(1004) x<-rcauchy(n,mu,s) loglik<-function(mu) { log(prod(dcauchy(x,mu,s))) } maxNR(loglik,start=median(x))$estimate Does anyone know how

Greetings, I use maxNR function under maxLik package to find the REML estimates of the parameters of variance components in heteroskedastic linear regression models. I assume that in the model there is additive/multiplicative/mixed heteroskedasticity and I need estimate the respective parameters of additive/multiplicative/mixed variance components. For my research purposes I make a

Hello everyone... We were trying to implement the Newton-Raphson method in R, and estimate the parameters a and b, of a function, F, however we can't seem to implement this the right way. Hope you can show me the right way to do this. I think what we want R to do is to read the data from the website and then peform maxNR on the function, F. Btw the version of R being used is "RGui for

Hi R-users, Does R has a topic on newton's method? Thank you for the info.

I am trying to solve an integral in R. However, I am getting an error when I am trying to solve for that integral. The equation that I am trying to solve is as follows: $$ C_m = \frac{{abs{x}}e^{2x}}{\pi^{1/2}}\int_0^t t^{-3/2}e^{-x^2/t-t}dt $$ [image: enter image description here] The code that I am using is as follows: a <- seq(from=-10, by=0.5,length=100) ## Create a function to compute

Hello again. Thank you for the comments. I have written these codes. iy=function(x) { res=NULL ress=0 for (i in (1:2)) { for (xx in x[i]) { fy=function(y) (exp(-exp(y+log(xx)))*(-exp(y+log(xx)))^2)/(1-exp(-exp(y+log(xx)))) res=c(res,integrate(fy,-6.907,-1.246)$value) ress=ress+res } } return(ress) } iy(c(1,1)) integrate(fy,-6.907,-1.246)$value In 1D optimize() works perfectly on iy(). However

Hello All, I have to create a variable that is a function of another one (already created), its cumulative distribution function and the integral of this cumulative distribution, with limits: 0 and the value of the variable. To be clear, I have the variable called “cip”. And its cdf called “cdfcip” I need to create the variable: bip = cip + ((1 – cdfcip)^4)*integral((1-cdf(u))^4*du, 0, value

Hi, Could somebody help me with the following. I want to calculate the integral over an implicit function. I thought to integrate over a function depending on uniroot. In previous topics I found a thread about finding the root of an integral. And that works. But the other way around, does not work. Does R support this? I included the following example. The function in the example is very easy

I have a question about running an optimization function on an existing LOESS function defined in R. I have a very large dataset (1 million observations) and have run a LOESS regression. Now, I want to run a Newton-Raphson optimization to determine the point at which the slope change is the greatest. I am relatively new to R and have tried several permutations of the maxNR and nlm functions with

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

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

Hi All, Can any one help to explain why min and max function couldn't work in the integrate function directly. For example, if issue following into R: integrand <- function(x) {min(1-x, x^2)} integrate(integrand, lower = 0, upper = 1) it will return this: Error in integrate(integrand, lower = 0, upper = 1) : evaluation of function gave a result of wrong length However, as min(U,V) =

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, I've got an ugly but fairly simple function: mdevstdev <- function(a){ l <- dnorm(a)/(1-pnorm(a)) integrand <- function(z)(abs(z-l)*dnorm(z)) inted <- integrate(integrand, a, Inf) inted[[1]]/((1- pnorm(a))*sqrt((1 + a*l - l^2))) } I wanted to quickly produce a graph of this over the range [-3,3] so I used: plotit <-function(x=seq(-3,3,0.01),...){

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

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, Can Maple function be exported to R? I have a jacobian matrix (4X4)?from maple in algebraic form which involve modified Bessel function of the first kind. I just wonder whether we can use algebraic form into R before the value of the parameters can be estimated. Thank you so much for your attention and help.

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)

Hi all, Can anyone please take a look at the following two functions. The answer does not seem to be right. Thank you very much! f1 <- function(x) {integrand <- function (x, mu){ dnorm(x, mean=mu, sd=1)*dnorm(mu, mean=2, sd=1) } integrate(integrand, -Inf, Inf,x)$val } f2 <- function(x) {integrand <- function (x, mu){

Estimada comunidad, nuevamente con algo que no se como hacer en R, pero aprendiendo .... El problema es el siguiente: 1. tengo un conjunto de 10 mil datos (n) cuyo valor va entre 0 y 10.000 a los que aplico una funcion sm.density() para obtener una especie de histograma pero con una curva que parece continua. 2. Una vez que obtengo esa curva necesito calcular el area bajo la curva en ciertos