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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

...(-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)$value [1] 1.387143 > integrate(dummy, -1000, 0)$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 i68...

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,

...9;eta2') simparj.fm <- nls(Y.simulated ~ Y.model(gN, MnmN, OptN, DIs, beta, eta1, eta2, Popn, Dmax, AWC, SumEp, PotYield3, Nsupply), start = simparj.st, trace =T) pr1<-profile(simparj.fm) # define a new profile function pr2<- function (fitted, which = 1:npar, maxpts = 100, alphamax = 0.01, delta.t = cutoff/5) { f.summary <- summary(fitted) std.err <- f.summary$parameters[, "Std. Error"] npar <- length(std.err) nobs <- length(resid(fitted)) cutoff <- sqrt(npar * qf(1 - alphamax, npar, nobs - npar)) outmat &...

...f.x1 <- sum(dnorm((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'...

...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: integrate(fm,0,x,maxpts = NULL, eps=0.01) works ok for everything I tried it for except x = 0 for some reason, hence the ifelse above. The problem is with inbeta. Trying inbeta(x) for any value of x other than 0 gives the error "Error in rep(no, length = leng...

...cons = adapt(2,c(-5,0,-.5),c(5,10,.5),f=unsc.post,max=5e+05,val=data) This produces the error: *** caught segfault *** address 0x7eaa8580, cause 'memory not mapped' Traceback: 1: .C("cadapt", as.integer(ndim), as.double(lower), as.double(upper), minpts = as.integer(minpts), maxpts = as.integer(maxpts), ff, rho = environment(), as.double(eps), relerr = double(1), lenwrk = as.integer(lenwrk), value = double(1), ifail = integer(1), PACKAGE = "adapt") 2: adapt(2, c(-5, 0, -0.5), c(5, 10, 0.5), f = unsc.post, max = 5e+05, val = data) On a perhaps related n...

...f.x1 <- sum(dnorm((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&...

...f.x1 <- sum(dnorm((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...

...ty element has been omitted the part of the args list of 'c' being evaluated was: (paste("Ifail=2, lenwrk was too small. -- fix adapt() !\n", "Check the returned relerr!"), "Ifail=3: ndim > 20 -- rewrite the fortran code ;-) !", "Ifail=4, minpts > maxpts; should not happen!", "Ifail=5, internal non-convergence; should not happen!", ) When it finishes: Warning messages: 1: Ifail=2, lenwrk was too small. -- fix adapt() ! Check the returned relerr! in: adapt(ndim = 1 + numcycles, lower = rep(lowlim.int, (numcycles + 2: NA/Inf replace...

Is there any way to know how the "dmvt" function computes the hypergeometric function needed in the calculation for the density of multivariate t distribution? -- View this message in context: http://r.789695.n4.nabble.com/hypergeometric-function-in-mvtnorm-tp4483730p4483730.html Sent from the R help mailing list archive at Nabble.com.

...ius_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 -- View this message in context: h...

...1 minor = 2.1 year = 2001 month = 01 day = 15 language = R > risk <- function(f,g,H,lower.limits,upper.limits) + { prob.of.fracture <- function(x) + { a <- x[1] + kc <- x[2] + f(a) * g(kc) * H(a,kc) } + adapt(2,lower.limits,upper.limits,minpts=200,maxpts=20000,prob.of.fracture,e ps=1e-3) } > risk(eifs.at.time.using.density(5000,eifs,1e-4,2),g,H,c(0.001,20),c(.5,60)) [1] 1.999471 value relerr minpts lenwrk ifail 28.39852 0.0003455776 627 2803 0 > > eifs.5000 <- eifs.at.ti...

...use the multiple comparison of Dunnett. It succeeded in upper case "example 1". However, the lower case "example 2" went wrong. In "example 2", the function pmvt return NaN, so I cannot show this simtest result. Is there any solution? (I changed the variable "maxpts" to a large number in front of the function pmvt ... but, the function mvt returned an error. ) -- example 1 ------------------------------- require(multcomp) Loading required package: multcomp Loading required package: mvtnorm [1] TRUE y <- as.vector(t$int) f <- as.factor(t$group1)...

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,

...eallocPts (pa=@0xbfffd7a0) at ANN.cc:124 #4 0x4030733d in ANN_interface (xp=0x8cd8280, eps=@0x8e2a550, qp=0x8e2a5c8, dnn=0x8d727f0, n_pts=@0x8dc7be8, k=@0x8dc7c08, dim=@0x8dc7c28, q_pts=@0x8dc7c48, bucket_size=@0x8dc7c68, insplit=@0x8dc7c88, inshrink=@0x8dc7ca8, priority=@0x8dc7cc8, maxpts=@0x8dc7ce8, nn=0x8ace0d0) at ANN_interface.cc:133 #5 0x808a557 in do_dotCode (call=0x8a3f098, op=0x81a7a5c, args=0x8a3d388, env=0x8a4326c) at dotcode.c:1310 #6 0x809136f in Rf_eval (e=0x8a3f098, rho=0x8a4326c) at eval.c:424 #7 0x8092a67 in do_set (call=0x8a3f044, op=0x819e8c4, args=0x8a...

Fedora 9 R 2.7.1 I tried to install R on my Linux system using install.packages("Rcmdr", dependencies=TRUE). I received many, many, many error messages. I hope someone can suggest a fix. The output from warnings() is listed below. A more detailed list of errors from one of the failed installations is listed below the warnings: > warnings() Warning messages: 1: In