similar to: feature request: optim() iteration of functions that return multiple values

For a solution that does not require any change to the original function being optimized, the following one-liner could be used, which converts existing functions to functions that return only the first element: returnFirst <- function(fun) function(...) do.call(fun,list(...))[[1]] Example: fr <- function(x) { ## Rosenbrock Banana function x1 <- x[1] x2 <- x[2] ans

Hi, I would like to know how to capture the console output from running an algorithm for further analysis. I can capture this using capture.output() but that yields a character vector. I would like to extract the actual numeric values. Here is an example of what I am trying to do. fr <- function(x) { ## Rosenbrock Banana function on.exit(print(f)) x1 <- x[1] x2 <- x[2]

Hi, I think that there something wrong with the 'constrOptim' max/minimization function because she doesn?t send extra arguments to 'optim' call. Fact: When I use optim in a f(x,theta)-like function, everything goes ok. But using constrOptim with the same function leads to error... Proof: Make a small change in the 'Rosenbrock Banana function' (taken from the Examples

In the documentation for 'optim' it gives the following function: fr <- function(x) { ## Rosenbrock Banana function x1 <- x[1] x2 <- x[2] 100 * (x2 - x1 * x1)^2 + (1 - x1)^2 } optim(c(-1.2,1), fr) When I run this code I get: $par [1] 1.000260 1.000506 I am sure I am missing something but why isn't 1,1 a better answer? If I plug 1,1 in the function it seems

Dear all, I am not fluent in R and am struggling to 1) apply a lm to a weight-size dataset, thus the model has to run separately for each species, each year; 2) extract coefs, r-squared, n, etc. The data look like this: year sps cm w 2009 50 16 22 2009 50 17 42 2009 50 18 45 2009 51 15 45 2009 51 16 53 2009 51 17 73 2010 50 15 22 2010 50 16 41 2010 50 16 21 2010

I've seen a number of problems like this over the years. The fact that the singular values of the Jacobian have a ration larger than the usual convergence tolerances can mean the codes stop well before the best fit. That is the "numerical analyst" view. David and Jeff have given geometric and statistical arguments. All views are useful, but it takes some time to sort them all out and

Hi all! I'm running some simulations and I need to estimate some paramaters with optim( ), in some cases optim stops with the next message: "L-BFGS-B needs finite values of 'fn' " I would like to know how to include and "if" condition when this happen, could it be something like: myfun <- optim(....) # run my function

Dear all, I have a function MYFUN which depends on 3 positive parameters TETA[1], TETA[2], and TETA[3]; x belongs to [0,1]. I integrate the function over [0,0.1], [0.1,0.2] and [0.2,0.3] and want to choose the three parameters so that these three integrals are as close to, resp., 2300, 4600 and 5800 as possible. As I have three equations with three unknowns, I expect the exact fit, i.e., the SS

How can I use a function with some additional input parameters in constrOptim? For example, something like fr <- function(x,a) { ## Rosenbrock Banana function x1 <- x[1] x2 <- x[2] a * (x2 - x1 * x1)^2 + (1 - x1)^2 } where the optimum is to be found w.r.t. x. Calling optim(c(-1.2,1), fr, NULL, a=100) works as expected, but I fail to provide the a=100 in the constrained case:

I am not as expert as John, but I thought it worth pointing out that the variable substitution technique gives up one set of constraints for another (b=0 in this case). I also find that plots help me see what is going on, so here is my reproducible example (note inclusion of library calls for completeness). Note that NONE of the optimizers mentioned so far appear to be finding the true best

I am trying to maximise a complicated loglikelihood function with the "optim" command. Is there some way to get to know the estiamtes at each iteration? When I put "control=list(trace=TRUE)" as an option in "optim", I just got the initial and final values of the loglikelihood, number of iterations and whether the routine has converged or not. I need to know the

Dear All, I am in the process of translating some of my functions into C and one such function sometimes get stuck when I applied optim. The pure R codes work fine but the translated C codes occasionally get stuck and I like to find out why. Is it possible to extract the parameters of function calculated in each step of the Nelder-Simplex algorithm, the trace option only produce the value of

Hello, If the signature of a method defines which generic it implements then I'm confused about why this minimal example I invented won't work : setGeneric("myFun", function(rs, ...){standardGeneric("myFun")}) setGeneric("myFun", function(cs, ...){standardGeneric("myFun")}) setMethod("myFun", "numeric", function(rs, colour =

I declared the environment of the function myfun to be NULL as follows: environment(myfun) <- NULL Later on I called that myfun and got an error message because the function index() in the zoo package was called inside myfun and was not visible: Error in myfun(args) : couldn't find function "index" I tried to use zoo::index() instead of index(), but that did not work. In fact,

Dear Rers, I have a function to barplot() a matrix, eg myfun <- function(x, ...) { barplot(x , ... )} (The real function is more complicated, it does things to the matrix first.) So I can do: m1 <- matrix(1:20,4) myfun(m1) myfun(m1, main="My title") I'd like to be able to add the number of rows of the matrix passed to the function to the "..." argument, eg

Hello R users, i'm wondering how to trigger variable creation. Whenever a variable is created i want my own function myFun(...) to be started. if (exists("x")) {rm(x)} # after removal of x # any of these calls x<-10 # should call myFun x=10 # should call myFun assign(x,10) # should call myFun etc.

Of course (and unsurprisingly) Duncan is correct. I see that behavior in R 3.1.0, as well as the modern ones Duncan mentioned. What I said is true, as far as it goes, but the symbol being resolved is FUN, so when looking for a function it doesn't find the function version of round. Did you perhaps have a function named FUN in your global environment? If so you are being bitten by what I

R> myfun <- function(x, ...) {x[...] <- 0; x} R> myfun(3) Error in myfun(3) : SubAssignArgs: invalid number of arguments It fails because no ... was passed. The workaround (and desired behavior) is: R> myfun <- function(x, ...) {if (missing(...)) x[] <- 0 else x[...] <- 0; x} R> myfun(3) [1] 0 Deja vu? This is the one piece of my PR#1110 (Oct 3, 2001) that I

Is there a way to call a function, and explicitly set an argument to 'not specified'? My situation is the following. I have a function which passes on most of its arguments to another function. The second function, myfun2, serializes all arguments and is out of my control. myfun <- function(...){ return(myfun2(...)); } now, the value for arguments of myfun are stored in variables.

Hi, on R version 2.15.1 (2012-06-22) (Platform: i686-pc-linux-gnu (32-bit)) sourced functions have srcref attached as an attribute. Are such data also available for S4 generics and methods? How? (See sample code below) Thank you. Bests, Renaud f <- textConnection( " f <- function(){} setGeneric('myfun', function(x, ...) standardGeneric('myfun'))