similar to: Profile on optim/nlm

Greetings, I use S+, Stata, SAS and R depending on the weather... The script file editors in S+, SAS and Stata all allow me to submit a portion of a developing script file to the running process. In R I have to use an external editor and either source the entire file or do lots of copy-and-pasting. Are there any editors out there which interface to R more closely and let me submit a section

I'm looking for an example of a simple R script that impliments a contrained nonlinear function using nlm or optim. I'm not exactly sure how to impliment the constraints within the objective function that is passed to nlm/optim. obj.func <- function( p ) { x(p) <- unconstrained obj function value if( constraint1 > something ) { obj.func <- x(p) } else {

This is a bit obscure but caused me some grief... R1.5.1/MS Windows There seems to be a peculiarity in legend associated with the use of expression text. It seems as if expression text is used in (eg) an mtext call then if the call to legend also includes expression text and a subscript then the legend box and line spacing depends on the value of cex used in the previous call to mtext,

I am facing a problem when trying to maximize the likelihood function. I am actually estimating a dynamic switching regression model using simulated likelihood approach. The likelihood function is estimated using Simulations and is extremely complex. It comprises of 16 parameters ,q1, q2, q3,.......q16. While attempting to maximize the likelihood function, using the functions nlm() and optim(),

Dear all, I just know how to solve an eaquation by using optim() or nlm(). But, now, I have three nonlinear equations, how could we use optim() or nlm() to solve  a system of nonlinear equations in R?  Thank you so much. Sincerely, Joe ___________________________________________________ 您的生活即時通 － 溝通、娛樂、生活、工作一次搞定！ [[alternative HTML version deleted]]

Dear R-users, I have just joint the list and much appreciate any thoughts on 2 issues. Firstly, I want to reproduce some minimization results conducted in MATLAB. I have suceeded with nlm and optim-method CG. I have been told that I should get also with other optim methods. Actually, I found the same results when testing a very straightforward equation. However with a more complicated model it

R2.0.1 (MS Windows) > list.files(myloc,"*.zip",full=T) [1] "P:/SARsoftware/Rlibraries/gnlm_0.1.zip" [2] "P:/SARsoftware/Rlibraries/lms2_0.2.zip" R2.1.0: > list.files(myloc,"*.zip",full=T) Error in list.files(path, pattern, all.files, full.names, recursive) : invalid 'pattern' regular expression Bug? or have I missed something

Hello, I am trying to use nlm to estimate the parameters that minimize the following function: Predict<-function(M,c,z){ + v = c*M^z + return(v) + } M is a variable and c and z are parameters to be estimated. I then write the negative loglikelihood function assuming normal errors: nll<-function(M,V,c,z,s){ n<-length(Mean) logl<- -.5*n*log(2*pi) -.5*n*log(s) -

There must be a simple answer. I want to plot an expression, where the expression is held in a string variable. The "obvious" solution along the lines of ex<-"x^2" plot( c(0,1), c(0,1), main=as.expression(ex) ) gives me the a title x^2 - ie doesn't treat it like an expression. I suspect I don't understand expressions properly. For the real problem I do need to

Hi, I have the following hypothetical optimization problem: -det(t(x-A%*%x1)%*%(x-A%*%x1)) where A,x,x1 are matrices. A coefficients and x and x1 are variable matrices or vectors. I tried to apply optim and nlm functions but I kept receive the following massage: Error in A%*%x1 : non-conformable arguments. The massage appears even the -det() can be calculated and the dimensions are checked. here

Hi everyone. I have a problem that I have been unable to determine either the best way to proceed and why the methods I'm trying to use sometimes fail. I'm using the pf() function in an optimization function to find a noncentrality parameter that leads to a specific value at a specified quantile. My goal is to have a general function that returns the noncentrality parameter that

Dear R users, I?m trying to optimize simultaneously two binomials inequalities (used in acceptance sampling) which are nonlinear solution, so there is no simple direct solution. Please, let me explain shortly the the problem and the question as following. The objective is to obtain the smallest value of 'n' (sample size) satisfying both inequalities: (1-alpha) <= pbinom(c, n, p1)

How about this one? If I set a variable in a data.frame with a two- part name including a dot (say y.pair), and if the variable with the name of the first part (y) doesn't but I ask for it's value I get the value of the two-part name. Ie set fred$x.pair and print the value of fred$x it gives me the value I set to fred$x.pair. Weird and somewhat disturbing! Maybe an example makes it

I've been trying to figure out how to get the names of the parameter vector variables when inside the function that nlm calls to return the objective function value: knls <- function( theta, eqns, data, fitmethod="OLS", instr=NULL, S=NULL ) { ## print( names( theta ) ) # returns NULL ## get the values of the parameters for( i in 1:length( theta ) )

Dear R-users, I am trying to find the MLEs for a loglikelihood function (loglikcs39) and tried using both optim and nlm. fredcs39<-function(b1,b2,x){return(exp(b1+b2*x))} loglikcs39<-function(theta,len){ sum(mcs39[1:len]*fredcs39(theta[1],theta[2],c(8:(7+len))) - pcs39[1:len] * log(fredcs39(theta[1],theta[2],c(8:(7+len))))) } theta.start<-c(0.1,0.1) 1. The output from using optim is

Dear R programming folks: I'm trying to finish off a package for non-linear simultaneous system estimation and I've been trying to figure out how to get the names of the parameter vector variables when inside the function that nlm calls to return the objective function value: knls <- function( theta, eqns, data, fitmethod="OLS", instr=NULL, S=NULL ) { ## print(

Hi there I am having trouble figuring out how to get an nlm function to report estimates for two parameter values in an estimation. The way I've got it goes something like this: f <- function (q, r) { here, I have a second loop which uses q, r to give me values for c, d below. a and b are already specified; this loop is a mass-balance function where I am trying to find values of q,

Hello, I am trying to compute MLE for non-Gaussian AR(1). The error term follows a difference poisson distribution. This distribution has one parameter (vector[2]). So in total I want to estimate two parameters: the AR(1) paramter (vector[1]) and the distribution parameter. My function is the negative loglikelihood derived from a mixing operator. f=function(vector)

Anybody out there successfully using the Salford Fortran compilers with R? I have created a DLL using the Salford FTN95 compiler and it works in as far I can dyn.load it, run the routines and get the right answers back. Unfortunately subsequently, sometime later, the Rgui crashes (access violation I think from the DrWatson log). The crashes depend on whether or not I paste the code as one

Hi, I was wondering if someone could give a brief, big picture overview of the difference between the two optimization functions nlm and nlminb. I'm not familiar with PORT routines, so I was hoping someone could give an explanation. Thanks, Angelo _________________________________________________________________ Instantly invite friends from Facebook and other social networks to join yo