similar to: Error in integrate

Dear listers, I am trying to fit a model using nlsList() using alternately a SSfol() selfstart function or its developped equivalent formulae. This preliminary trial works well mydata<-groupedData(Conc~Tps|Organ,data=mydata) mymod1<-nls(Conc~SSfol(Dose,Tps,lKe,lKa,lCl),data=mydata) as well as a developped form: mymod2<-nls(Conc~Dose * exp(lKe+lKa-lCl) *

Dear R users, If I have to combine plots which have the same independent and dependent variables in one graph. Which command should I use? Any example? Can I use "panel"? Your help will be deeply appreciated. Thanks! -Vivien Chen- [[alternative HTML version deleted]]

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 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) =

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

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)

Dear R useRs, i try to integrate the following function for many values "integrand" <- function(z) { return(z * z) } i do this with a for-loop for(i in 2:4) { z <- integrate(integrand, i-1, i)$value cat("z", z, "\n") } to speed up the computation for many values i tried vectors in integrate to do this. vec1<-1:3 vec2<-2:4

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

Dear list, I may have found a bug in model.frame.default (called by the lm function). The problem arises in my R dev version but not in my R 2.4.0. Here is my config : > version _ platform x86_64-unknown-linux-gnu arch x86_64

Hi there. Thanks for your time in advance. I am using R 2.2.0 and OS: Windows XP. My final goal is to calculate 1/2*integral of (f1(x)^1/2-f2(x)^(1/2))^2dx (Latex codes: $\frac{1}{2}\int^{{\infty}}_{\infty} (\sqrt{f_1(x)}-\sqrt{f_2(x)})^2dx $.) where f1(x) and f2(x) are two marginal densities. My problem: I have the following R codes using "adapt" package. Although "adapt"

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 All, Hello! I have some questoins in R programming as follows: Question 1- How to take the integral of this function with respect to y, such that x would appear in the output after taking integral. f(x,y)=(0.1766*exp(-exp(y+lnx))*-exp(y+lnx))/(1-exp(-exp(y+lnx))) y in (-6.907,-1.246) It is doable in maple but not in R. At least I could not find the way. p.s: result from maple is:

Greetings List, I'm having some trouble with the use of the names function in a formula. Below is an example of something that works (i.e first line), and the second line is the same formula which doesn't. I want to be able to reference the column of the dataC table so I can run the variogram iteratively with a loop. > v<-variogram(A1~1,loc=~x+y, dataC) >

hi all i have a function that uses two inputs, say xdata and ydata. An example is the following, simple1<-function(xdata,ydata) { ofit<-lm(ydata~xdata) list(ofit) } say i use arbitray number for xdata and ydata such that D = x1 x2 y 1 1 10 2 6 6 3 10 7 x<-D[,1:2] and y<-D[,3] if one uses these inputs and rund the program we get the following: >simple(xdata=x,ydata=y)

I hope you can help me. I am new to "R" and am working through the example of quantile regression analysis in the paper by Roger Koenker (quantile regression in R: a Vignette. I got to page 6 and in trying to execute the following code I received the error below. I have searched on the web and while I have found similar error messages, I have not been able to ascertain the root cause.

I'm trying to learn to use manova(), and don't understand why none of the following work: > data(iris) > fit <- manova(~ Species, data=iris) Error in lm.fit(x, y, offset = offset, singular.ok = singular.ok, ...) : incompatible dimensions > fit <- manova(iris[,1:4] ~ Species, data=iris) Error in model.frame(formula, rownames, variables, varnames, extras,

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){

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-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