search for: functn

...ng 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, but never mind that for the moment. Perhaps some kind person could explain what I am doing wrong here? The help page says "functn an R function which should take a single vector argument and possibly some parameters and...

...There is one problem I encountered when I used ADAPT to compute some 2-D integral w.r.t beta density. For example, when I try to run the following comments: fun2<-function(theta){return(dbeta(theta[1],0.005,0.005)*dbeta(theta[2],0.005,0.005))} int.fun2<-adapt(ndim=2,lo = c(0,0), up = c(1,1),functn = fun2,eps = 1e-4) It seems it will take very long time to run. Acturally, I stopped the program after it was running for like 20 minutes. I thought this might be due to the inclusion of the lower and upper in to the integral computation, so I tried to change the lower and upper limits: fun2<...

...ut, sigma = matrix(c(.1, 0, 0, .1), nrow = 2, ncol = 2, byrow = FALSE)) } require(mvtnorm) require(adapt) bottomB <- -5*sqrt(.1) topB <- 2 + 5*sqrt(.1) areaB <- (topB - bottomB)^2 unscaled.Po.in.a <- adapt(2, lo = c(bottomB, bottomB), up = c(topB, topB), minpts = 1000, eps = 1e-4, functn = trial) (1/areaB)*unscaled.Po.in.a$value ## FINISH PROGRAM I tried to run the program again changing a.) sigma in the trial function, b.) upper in the trial function, and c.) the bounds of integration; that is, bottomB and topB. The new program is below: ## START PROGRAM trial <- functi...

...ndary to be too small integrate causes a segmentation fault: > library(integrate) > integrate(dummy, -100, 0)$value [1] 1.387143 > integrate(dummy, -1000, 0)$value [1] NaN Warning message: Ifail=1, maxpts was too small. Check the returned relerr! in: adapt(1, lower, upper, minpts, maxpts, functn, eps, ...) > integrate(dummy, -10000, 0)$value Segmentation fault I'm running R.1.2.0 on Debian Linux. Regards Achim > version _ platform i686-pc-linux-gnu arch i686 os linux-gnu system i686, linux-gnu status...

...ng it integrates a scalar function over a multidimensional rectangle. I have integrand of several variable and upper, lower limit too variable. I wanted to see the result using adapt (though it is not for this purpose, I suppose) Func<-function(x){(x[1]*x[2])} adapt(2, lo=c(0,1), up=c(1,x[1]), functn=Func) it is not giving any error(it should, if it is not the correct way of putting up) but also not giving correct result. Is there any package to handle multiple integration in R?? Thanking you, with best regards, N. Dey

...where some of the boundaries are functions of the other variables? require(adapt) fn<-function(z,y,x) {exp(x^3+y^4+x^2*y+x*z^2+y/z)} x<-runif(200);y<-runif(200);z<-runif(200); c1<-.5;c2<-5;M<-100; #M to represent infinity i1<-adapt(3,lo=c(.0001,0,0),up=c(M,c1*z,c2/y),functn=fn)$value print(i1); Thanks, -- Davood Tofighi [[alternative HTML version deleted]]

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 change of variables to avoid this problem and it didn?t help. The command adapt calls a fortran routine, but I don?t know fortran enough to fix the problem. Can someone help me? Thanks a lot Rodrig...

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 some traps in my code to handle them correctly. I apologize for not including a reproducible example in this query, but the...

...x2, theta, param))} / 10000 kernel1 <- function(theta, param) { exp(loglik(theta, param)) + log(10000)} kernel2 <- function(theta, param) {( exp(loglik(theta, param)) + log(10000)) * gm(theta, param) } kernel2(theta0, param0) adapt(4, lower = c(0, 0, 0, 0), upper = c(1, 1, 1, 1), functn = kernel2(theta0, param0)) So I am trying to integrate the posterior density with four different parameters. But I cannot do anything to get the adapt function to work.

...-(2*index-0.324)*(radiusb/radius_eff)^(1/index))*(1+(((majaxis_pix^2)+(radiusb^2)-2*majaxis_pix*radiusb*cos(-thita)+(ellip^2-2*ellip)*((radiusb*sin(thita))^2))/(alpha^2)))^(-vita) return(counts2) } sersic=function(p) { counts0=p[1] index=p[2] radius_eff=p[3] value1=adapt(2,c(0,0),c(2*pi,200),functn=intensity,minpts=1000,maxpts=NULL,eps=0.01,counts0=counts0,index=index,radius_eff=radius_eff) test=value1$value f=sum(((counts-test)/countserr)^2) return(f) } out<-nlminb(c(16000.0, 3.0,10.0), sersic) ##############End of the code Any suggestions are welcome, Thank you, Marina -- Vi...

...m((x1.eval-x1)/h1))/(n*h1) f.x2 <- sum(dnorm((x2.eval-x2)/h2))/(n*h2) # Return the integrand # return((sqrt(f.x1)-sqrt(f.x2))**2) } estimate<-0.5*adapt(1, lo=lo.default, up=up.default, minpts=minpts.default, maxpts=maxpts.default, functn=integrand, eps=eps.default, x1, x2,h1,h2)$value But when I used it for one-dimension, it failed. Some of my colleagues suggested getting rid of "x2.eval" in the "integrand" because it is only one integral. But after I changed it, it still didn't work. R gave the error msg:...

I find the one-dimensional "integrate" very helpful, but often enough I stumble into problems that require two (or more)-dimensional integrals. I suppose there are no R functions that can do this for me, "directly"? The ideal thing would be to be able to define say f <- function(x) { x1 <- x[1] x2 <- x[2] sin(x1*x2)*exp(x1-x2) } and then write say integrate(f,

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!

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.

...val-x1)/h1))/(n*h1) f.x2 <- sum(dnorm((x2.eval-x2)/h2))/(n*h2) # Return the integrand # return((sqrt(f.x1)-sqrt(f.x2))**2) } estimate<-0.5*adapt(1, lo=lo.default, up=up.default, minpts=minpts.default, maxpts=maxpts.default, functn=integrand, eps=eps.default, x1, x2,h1,h2)$value But when I used it for one-dimension, it failed. Some of my colleagues suggested getting rid of "x2.eval" in the "integrand" because it is only one integral. But after I changed it, it still didn't work. R gave the error ms...

...val-x1)/h1))/(n*h1) f.x2 <- sum(dnorm((x2.eval-x2)/h2))/(n*h2) # Return the integrand # return((sqrt(f.x1)-sqrt(f.x2))**2) } estimate<-0.5*adapt(1, lo=lo.default, up=up.default, minpts=minpts.default, maxpts=maxpts.default, functn=integrand, eps=eps.default, x1, x2,h1,h2)$value But when I used it for one-dimension, it failed. Some of my colleagues suggested getting rid of "x2.eval" in the "integrand" because it is only one integral. But after I changed it, it still didn't work. R gave the error msg:...

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

Hello, I apologize for eventual double-posting. I am trying to integrate a 2-dimensional function that already calls the function adapt. More precisely, I am calling adapt(2,lower=c(-100,-100),upper=c(100,100),functn=function(s){1-exp(-50*Unc enteredGauss(c(-10,10,-10,10),60,s)}) where UncenteredGauss is given by the following code in R: UncenteredGauss=function(limsamp,sigma2,s) { int=adapt(2,lower=c(limsamp[1],limsamp[3]),upper=c(limsamp[2],limsamp[4]),fu nctn=function(u){h(sigma2,s,u)}) value=int...

...[i] +thmu*(e3[i])) Pni<- (y$Ch1[i]*exp(U1) + y$Ch2[i]*exp(U2)+ y$Ch3[i]*exp(U3))/(exp(U1)+exp(U2)+exp(U3)) fe<- exp((-e1[i]*e1[i]-e2[i]*e2[i]-e3[i]*e3[i])/(2*r)) fv<- exp((-v[1]*v[1]-v[2]*v[2])/(2*s)) prelik<- Pni*fe*fv return(prelik) } int[i]<- adapt(2,lo = c(-4,-4), up = c(4,4), functn= lstarpre, eps=0.01)$value print(int[i]) lik[i]<- log(max(1E-20,int)) print(lik[i]) } #End Loop logl<-sum(lik) return(-logl) } p<-optim(c(0,0,0,0,0,0,0,0,0,0,0),mnl.lik,y=DATA,method="BFGS",hessian=T, control = list(maxit=6000, temp=2000, trace=4))

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,