similar to: inconsistent results when calling functions with other func (PR#869)

Hi all I was wondering if someone could help me. I have to estimate some parameters, so I am using the function nlm. Inside this function I have to integrate, hence I am using the function adapt. I don't understand why it is giving the following warnings: At the beginning: Warning: a final empty element has been omitted the part of the args list of 'c' being evaluated was:

R-listers, In using the adapt function, I am getting the following warning: Ifail=2, lenwrk was too small. -- fix adapt() ! Check the returned relerr! in: adapt(ndim = 2, lower = lower.limit, upper = upper.limit, functn = pr.set, Would someone explain what the 'lenwrk' value indicates in order to help diagnose this issue. Also, what are the possible codes for Ifail, so I can set

I'm having trouble with adapt. I'm trying to use it in a Bayesian setting, to integrate the posterior distribution, and to find posterior means. I tried using the following script, and things went ok: data = rnorm(100,0.2,1.1) data = c(data,rnorm(10,3,1)) data = data[abs(data)<2*sd(data)] prior = function(x){ dgamma(x[2],shape=2,scale=1)*dnorm(x[1],0,.5) } liklihood =

I tried to integrate numerically a function wich is similar to the following: > dummy <- function(x) { exp(-1*x) * dnorm(x) } > dummy(-100) [1] 0 > dummy(-1000) [1] NaN > dummy(-10000) [1] NaN If I choose the lower boundary to be too small integrate causes a segmentation fault: > library(integrate) > integrate(dummy, -100, 0)$value [1] 1.387143 > integrate(dummy, -1000,

Dear People, I'm trying to use the function adapt, from the adapt library package, which does multidimensional numerical integration. I think I must be using the wrong syntax or something, because even a simple example does not work. Consider foo <- function(x){x[1]*x[2]} and adapt(2, lo = c(-1,-1), up = c(1,1), functn = foo) This simply hangs. A more complicated example crashes R,

Hi all, I need to calculate a multidimensional integration on R. I am using the command "adapt" (from library adapt), although sometimes I get the following error message: Ifail=2, lenwrk was too small. -- fix adapt() ! Check the returned relerr! in: adapt(3, linf, lsup, functn = Integrando1) I guess it happens because the domain of integration is too small, although I tried a

Dear r-users, Is there any command in R allowing to evaluate a double integral? for instance let say I want to evaluate the following integral: integrate[lo=(0,1),up=(2,3)] f(x,y)=x^2+y^2 where lo is the vector of lower bounds and up that of upper bounds. I thaught the function "adapt" would work but it did not. Many thanks, Dominique K.

how does one numerically intergate the following: A=function(x,y) { xy } over the range: 2<x<0 4<y<10 say. ie how would one set up the integrate function? i forgot!

Hi, I need to integrate a 2D function over range where the limits depend on the other e.g integrate f(x,y)=x*y over {x,0,1} and {y,x,1}. i.e \int_0^1 \int_x^1 xy dydx I checked adapt but it doesn't seem to help here. Are they any packages for this sort of thing? I tried RSitesearch but couldn't find the answer to this. Many thanks for you help. Regards Saptarshi Saptarshi Guha

Hi all, Running R 0.90.1 on a RH 6.1 system. Installation of the integrate_2.1-2 package went smoothly. My code contains a loop in which integrate() is called several times in each pass. I get a segmentation fault after what seems to be a random number of calls to integrate(). Debug output shows: Program received signal SIGSEGV, Segmentation fault. promiseArgs (el=0x40276414,

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"

I am trying calculate a probability using numerical integration. The first program I ran spit out an answer in a very short time. The program is below: ## START PROGRAM trial <- function(input) { pmvnorm(lower = c(0,0), upper = c(2, 2), mean = input, sigma = matrix(c(.1, 0, 0, .1), nrow = 2, ncol = 2, byrow = FALSE)) } require(mvtnorm) require(adapt) bottomB <- -5*sqrt(.1) topB <-

Hello all, I am trying to minimize a function which contains a double integral, using "nlminb" for the minimization and "adapt" for the integral. The integral is over two variables (thita and radiusb) and the 3 free parameters I want to derive from the minimization are counts0, index and radius_eff. I have used both tasks in the past successfully but this is the first time

Hi people, Does anybody know some Density-Based Method for clustering implemented in R? Thanks, Fernando Prass _______________________________________________________

Hi there. Thanks for your time in advance. 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 estimated marginal densities. My problem: I have the following R codes using "adapt" package. Although "adapt" function is mainly designed

Hi there. Thanks for your time in advance. 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" function is mainly designed for more

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Suppose I have the following dataframe called test: test<-data.frame(year=rep(1990:2003,5),id=gl(5,length(1990:2003)),eif=as.vector(sapply(1:5,function(z){a<-rep(0,length(1990:2003));a[sample(1:length(1990:2003),sample(1:2,1))]<-1;a}))) year id eif 1990 1 0 1991 1 0 1992 1 0 2000 1 1 1994 1 0 1995 1 0 2001 1 0 1997 1 1 .... I want to create a new variable in

Hi everyone, Please forgive me if my question is simple and my code terrible, I'm new to R. I am not looking for a ready-made answer, but I would really appreciate it if someone could share conceptual hints for programming, or point me toward an R function/package that could speed up my processing time. Thanks a lot for your help! ## My dataframe includes the variables 'year',

Dear R people, There is probably a simple explanation for the following, but I have been unable to come up with one. I want to integrate x(1-x)^{-1/3} over intervals of the form [0,a] where a is between 0 and 1. Hence, consider: fm <- function(x) ifelse(x==0 | x==1 ,0,(x*(1-x))^(-1/3)) inbeta <- function(x) { ifelse(x==0,0,integrate(fm,0,x,maxpts = NULL, eps=0.01)) } Comments: