search for: minpts

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

...= major = 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 <-...

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

...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 <- 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...

...the marginal densities 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 change...

...se 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 i686 os linux-gnu system i686, linux-gnu status...

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,

...ginal densities 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 cha...

...ginal densities 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 chang...

...a final empty 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...

...{ prior(x)*liklihood(x,val) } 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 =...

...(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 -- View this message i...

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.

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

...scovered training clusters I am done with Step1 but pretty much stuck after that , Anyone knows how to proceed on the above Below is the code i am using for Step 1 ) --------------- library('fpc') x <- read.table("file.dat" , sep=",") d <- dbscan(x,eps = 1.9, MinPts=3,showplot = 2); Plot(d); --------------- I am fairly new to R , started a week back , but covered quite a few online resources without success If anyone knows of a better approach of what i am trying to achieve then please let me know Thanks & Regards Kapil [[alternative HTML versi...

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,