search for: bfgs

Dear kind R-experts. Does anybody have an experience to use optim function? If yes, what is the main difference between two method "BFGS" vs "L-BFGS-B"? I used "BFGS" method and got what I wanted. But when I used "L-BFGS-B" the error message said that "L-BFGS-B needs finite values of fn". So that means "BFGS" method can handle even if fn function is infinite value? What I reall...

Hi all, I'm trying to figure out the effective differences between BFGS and L-BFGS-B are, besides the obvious that L-BFGS-B should be using a lot less memory, and the user can provide box constraints. 1) Why would you ever want to use BFGS, if L-BFGS-B does the same thing but use less memory? 2) If i'm optimizing with respect to a variable x that must be non-nega...

...y <- length(x):1 val <- sum((yy*x)^2)*fscale } grt <- function(x, fscale=10){ nn <- length(x) yy <- nn:1 # gg <- rep(NA,nn) gg <- 2*(yy^2)*x*fscale gg } npar <- 4 lower <- -Inf l2 <- rep(-Inf,npar) a1 <- optim(x0, fnt, grt, lower=lower, method="BFGS") # works a1 a1a<- optim(x0, fnt, grt, lower=l2, method="BFGS") # changes method! a1a The first call uses BFGS method without warning. The second gives a warning that L-BFGS-B should be used, and from the output uses this. This is a bit of an edge case. My own preference would b...

With the exception of "L-BFGS-B", all of the other optim() methods return the value of the function when they are given a trivial function (i.e., one with no variable arguments) to optimize. I don't think this is a "bug" in L-BFGS-B (more like a response to an undefined condition), but it leads to a bug in s...

...one of the methods I tried after Ravi directed me to optimx. It returned NAs for essentially everything. See my email of this subject stamped 4:43 PM Central time = 21:43 UTC. 2. It would be interesting to know if the current algorithm behind optim and optimx with method='L-BFGS-B' incorporates Morales and Nocedal (2011) 'Remark on ?Algorithm 778: L-BFGS-B: Fortran Subroutines for Large-Scale Bound Constrained Optimization?'. I created this vignette and started this threat hoping that someone on the R Core team might decide it's worth checking things l...

...nrow(X)> p<-ncol(X)> n[1] 5> p[1] 6> > v<-rep(0,p-1)> v[1] 0 0 0 0 0> > fn1<-function(v) {+ a<-sum(v*v)+ u<-v/sqrt(1+a)+ b<-sum(u*u)+ u[length(v)+1]<-sqrt(1+b)+ c<<- X %*% u # also I try c<- X %*% u+ fn1<- - optim(c(0,1),fn2,NULL,method="BFGS",c)$value+ }> > > fn2<-function(par){+ fn2<- -length(c)*log(par[2])+sum(log(par[2]*par[2]+(c-par[1])*(c-par[1])))+ }> optim(v,fn1,NULL,method="BFGS",X)Error in fn(par, ...) : unused argument(s) (c(-0.277693546148993, -0.091468312551809, -0.99167995523182, -1.5400...

...4.4, 4.8, 5.9, 6.8) x <- log10(x) fr <- function(c, alpha, beta) { P <- c + (1-c) * pnorm(alpha + beta * x) P <- pmax(pmin(P,1),0) -(sum(log(choose(n,r))) + sum(r * log(P)) + sum((n -r)* log(1-P))) } fit <- mle((fr), start = list(c =0.2, alpha = 0, beta =0.1), method = "L-BFGS-B") I got: Error in optim(start, f, method = method, hessian = TRUE, ...) : L-BFGS-B needs finite values of 'fn' When I change "L-BFGS-B" to "BFGS" or anything else that optim() support, there's no any error message. What's wrong? Any suggestions will...

...am working on an optimization with R by evaluating a likelihood function that contains lots of Gamma calculations (BGNBD: Hardie Fader Lee 2005 Management Science). Since I am forced to implement lower bounds for the four parameters included in the model, I chose the optim() function mith L-BFGS-B as method. But the likelihood often returns inf-values which L-BFGS-B can't deal with. Are there any other options to implement an optimization algorithm with R accounting for lower bounds and a four parameter-space? Here is the error message I receive (german): -- > out=optim(c(.1,....

...prising 148 entries: fn<-function(c,psi,alpha) { s1<-sum(for(i in 1:n){(c[i]-(psi^(-1/alpha)*(lag(c[i],-1))))^2* (lag(c[i],-1)^((-2)*(alpha+1)) )}); s2<- sum(for(m in 1:n){log(lag(c[m],-1)^(((2)*alpha)+2))}); constant-(74*s1)-(1/2)*s2} In particular I want to use the BHHH and the BFGS algorithms. I have found the following packages that can be used for the task: *mle{stats4}, optim{stats}, maxBHHH{micEcon}, maxBFGS{micEcon}*. I have documented some of my attempts below ((a) package name (b) usage (c) my attempt and corresponding error). In all humility I apologise for any bad c...

The the use of optim with the L-BFGS-B method for the following simple function gives erroneous results. Any help appreciated! Best, Bob Reilly # Code: V=function(p){ p1=p[1];p2=p[2] y=p1*p2-.4*(p1+p2) return(-y)} p=c(.2,.2) # p=c(.8,.8) max=optim(p,V,method = "L-BFGS-B",lower=c(0,0),upper=c(1,1)) max1=optim(max$par,V...

Dear R Users/Experts, I am using a function called logitreg() originally described in MASS (the book 4th Ed.) by Venebles & Ripley, p445. I used the code as provided but made couple of changes to run a 'constrained' logistic regression, I set the method = "L-BFGS-B", set lower/upper values for the variables. Here is the function, logitregVR <- function(x, y, wt = rep(1, length(y)), intercept = T, start = rep(0.1, p), ...) { #-------------------------------------------# # A function to be minimized (or maximized) # #--------------------------...

I sent this in first on 30 July. Now that UseR! is over I'm trying again (slightly extended version from last time). With R 2.5.1 or R 2.6.0 (2007-08-04 r42421) "L-BFGS-B" behaves differently from all of the other optim() methods, which return the value of the function when they are given a trivial function (i.e., one with no variable arguments) to optimize. This is not a bug in L-BFGS-B (more like a response to an undefined condition), but it leads to a bug...

Hello: The development version of Ecdat on R-Forge contains a vignette in which optim(?, method=?L-BFGS-B?) stops with an error message while violating the lower bound. To see all the details, try the following: install.packages("Ecdat", repos="http://R-Forge.R-project.org") Then do "help(pac=Ecdat)" -> "User guides, package vignettes and ot...

Dear All, I am trying to solve the optimization problem below, but I am always getting the following error: Error in optim(rep(20, nvar), f, gr, method = "L-BFGS-B", lower = rep(0, : L-BFGS-B needs finite values of 'fn' Any ideas? Thanks in advance, Paul ----------------------------------------------- k <- 10000 b <- 0.3 f <- function(x) { n <- length(x) r <- sum((b^(0:(n-1)))*log(x)) - 2000000*(sum(x)-k)^2 retu...

...the new query below. Dear R Users/Experts, I am using a function called logitreg() originally described in MASS (the book 4th Ed.) by Venebles & Ripley, p445. I used the code as provided but made couple of changes to run a 'constrained' logistic regression, I set the method = "L-BFGS-B", set lower/upper values for the variables. Here is the function, logitregVR <- function(x, y, wt = rep(1, length(y)), intercept = T, start = rep(0, p), ...) { #-------------------------------------------# # A function to be minimized (or maximized) # #--------------------------------...

Dear R-er, For a non-linear optimisation, I used optim() with BFGS method but it stopped regularly before to reach a true mimimum. It was not a problem with limit of iterations, just a local minimum. I was able sometimes to reach better minimum using several rounds of optim(). Then I moved to optimx() to do the different optim rounds automatically using &quot...

Hi R-help! I'm trying to understand how R's nlm function updates its estimate of the Hessian matrix. The Dennis/Schnabel book cited in the references presents a number of different ways to do this, and seems to conclude that the positive-definite secant method (BFGS) works best in practice (p201). However, when I run my code through the optim function with the method as "BFGS", slightly different estimates are produced to that of nlm: > optim(strt,jointll2,method="BFGS",hessian=T)$par -0.4016808 0.6057144 0.3744790 -7.18...

Hi. I just noticed the paper by Morales and Nocedal Remark on "Algorithm 778: L-BFGS-B: Fortran Subroutines for Large-Scale Bound Constrained Optimization". TOMS 2011; 38(1): 7 http://www.ece.northwestern.edu/~morales/PSfiles/acm-remark.pdf which describes a couple of improvements (speed and accuracy) to the original Netlib code which AFAICT is that still used by optim()...

...ely, all the optimal values fall in their range of possible value. But to be rigourous, I should perform a box-constrained optimization. Then, I do so with the following command (in fixing the lower and upper args and not): optim(c(200,60,500,300,700),test,control=list(fnscale=-1),method="L-BFGS-B",lower=c(200,20,300,200,400),upper=c(500,60,500,300,700))$par [1] 200 60 500 300 700 optim(c(200,60,500,300,700),test,control=list(fnscale=-1),method="L-BFGS-B")$par [1] 200.00000 60.00007 500.00000 300.00000 700.00000 Here the result I get is wrong, and in fact it is more o...

...>>>> Spencer Graves <spencer.graves at prodsyse.com> >>>>> on Sat, 8 Oct 2016 18:03:43 -0500 writes: [.............] > 2. It would be interesting to know if the > current algorithm behind optim and optimx with > method='L-BFGS-B' incorporates Morales and Nocedal (2011) > 'Remark on ?Algorithm 778: L-BFGS-B: Fortran Subroutines > for Large-Scale Bound Constrained Optimization?'. I > created this vignette and started this threat hoping that > someone on the R Core team might decide...