search for: stepmax

...ion that passes the optional arguments to the objective function), but I presume this would be cleaner and faster if implemented at a lower level ... nlm2 <- function(f, p, hessian=FALSE, typsize=rep(1,length(p)), fscale=1, print.level=0, ndigit=12, gradtol=1e-6, stepmax=max(1000 * sqrt(sum((p/typsize)^2)), 1000), steptol=1e-6, iterlim=100, check.analyticals=TRUE, ...) { tmpf <- function(x) { f(x,...) } nlm(tmpf,p,hessian=hessian,typsize=typsize,fscale=fscale,print.level=print.level, ndigit=ndigit,gradtol=gradtol,stepmax=stepmax,s...

...ll to nlm(). This can be replicated by: FixedRemovals<-1836180125888 AbStageInitial<-2223033830403 Rates<- 0.3102445 nlm(function(rootM,Abund,Loss,OtherM) {(Loss-(rootM/(rootM+OtherM)* (1-exp(-(rootM+OtherM)))* Abund))^2} ,0.001,print.level=0,fscale=0, gradtol=1E-10, stepmax = 100.0 ,Loss=FixedRemovals ,Abund=AbStageInitial ,OtherM=Rates)$estimate ___________________________________________________________________________ Australian Antarctic Division - Commonwealth of Australia IMPORTANT: This transmission is intended for the addressee only. If yo...

...oc.time() > sink("out22031001.txt") > > fmainsimbiasP(10000,100) proc.time()-ptm *** caught segfault *** address 0x18, cause 'memory not mapped' Traceback: 1: nlm(f = fprof_deriv, x = x, p = parHInt, b = parFIX, hessian = T, iterlim = 2000, check.analyticals = F, stepmax = 10) 2: doTryCatch(return(expr), name, parentenv, handler) 3: tryCatchOne(expr, names, parentenv, handlers[[1]]) 4: tryCatchList(expr, classes, parentenv, handlers) 5: tryCatch(expr, error = function(e) { call <- conditionCall(e) if (!is.null(call)) { if (identical(call[[1]], quo...

I am trying to view the source code of the function nlm in the stats package of R 2.4.1. I downloaded the source from CRAN and opened nlm.R, and it calls a .Internal function: .Internal(nlm(function(x) f(x, ...), p, hessian, typsize, fscale, msg, ndigit, gradtol, stepmax, steptol, iterlim)) This is the same thing I saw when entering the function name at the R command prompt. Where will I find the actual code? Thanks.

...erent R function. optimize(f=Low.Lim.NC.F, lower=LL.0, upper=50, maximum=FALSE, tol=tol, alpha.lower=alpha.lower, F.value=F.value, df.1=df.1, df.2=df.2) # Try to accomplish the same task with a different R function. nlm(f=Low.Lim.NC.F, p=LL.0, fscale=1, print.level = 0, ndigit=12, gradtol = 1e-6, stepmax = max(1000 * sqrt(sum((LL.0/10)^2)), 1000), steptol = 1e-6, iterlim = 1000, check.analyticals = TRUE, alpha.lower=alpha.lower, F.value=F.value, df.1=df.1, df.2=df.2) # The answer in each case is 3.0725. Thus, a noncentral F with # 5 and 200 df with a noncentrality parameter 3.0725 has at its .975...

Hi Apart from nlm() with the stepmax= argument, is there any other >1 dimensional minimisation function where I can limit the step size dynamically. With the NAG routine E04NBF (I think) I used to bound the size of the next step using a*arctan(x/a) tricks where a function was particularly difficult near a boundary and thus 's...

Hi Everyone, Is there a simple way to force nlm to take larger initial steps? Setting print.level = 2 allows me to inspect the step size at each iteration, but I appear not to have made any appreciable impact on it by changing values of typsize, fscale, steptol or stepmax. The steps repeatedly come out tiny, 1e-9 typically, and the algorithm is terminating not because the gradient is zero (it is not, according to the numerical values) but because the function value is not changing between iterations. Am I missing something obvious? Many thanks, Jonathan. Jonatha...