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...but defining a temporary function 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,gra...

...owed it to a call 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 addres...

...ill had not converged after 100 iterations. What might be done to improve the performance of something like "nlm" without substantially increasing the overhead for other problems? Thanks. spencer graves ############################# nlm. <- function(f=fgh, p=c(-1.2, 1), gradtol=1e-6, steptol=1e-6, iterlim=100){ # R code version of "nlm" # requiring analytic gradient and hessian # # Initial evaluation f.i <- f(p) f0 <- f.i+1 # Iterate for(i in 1:iterlim){ df <- attr(f.i, "gradient") # Gradient sufficiently small? if(sum(df^...

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.

...task with a different 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...

...ct, theta15, 0.5 con -> prev, gam5, 0.8 prev -> enf, gam6, 0.4 sem.enf.rq <- sem(ram = mdl.rq, S = hcor(dx), N = nrow(dx), obs.v = names(dx), raw = F, fixed = names(dx)[4:6], par.size = 's', maxiter = 1e3, analytic = F, gradtol = 1e-10) ##set raw to False summary(obj = sem.enf.rq, dig = 3, conf = 0.9) Respectfully, Frank Lawrence

...st of cases. I tried to change the optional parameters in the nlm call but this does not help to achieve code=1. What may be a reason for such situation? Could I think that the obtained estimates are what I am looking for? I am using R 1.9.1: nlm(N.Loglik,initial.values,fscale=1,print.level = 1, gradtol = 1e-6,steptol = 1e-6,iterlim = 500,y=y) Much thanks, Victoria. [[alternative HTML version deleted]]