similar to: environment confusion

Thank you very much. now, i call mle(minuslogl=loglik, start=start, method <<- method, fixed=list()) in the mle.wrap() function, and the profile.mle() worked. however, it created a variable named "method" in user workspace. if there had been a variable with same name, then the value of that variable would be destroyed. Is there a way to avoid that happen? Thanks again.

I am having some trouble getting the persp() package to change the x and y axis on a 3d plot. It defaults to the [0,1] interval and when I try to change it I get errors. Example: This works: ------------ D <- c(1,2,3,4,5,6,7,8,9,10) M <- c(11,12,13,14,15,16,17,18,19,20) DM <- cbind(D,M) persp(DM, theta = 40, phi = 30, expand = 0.5, col = "lightblue", ltheta = 120,

Dear R-users, I'd like to plot a three-dimensional surface and at the meantime I'm using an array. I would like to have the values of my first matrix in the heights of the plot and the colors of the single facet taking into account the second matrix. I hope that the next code will help all of you to understand better my issue, Thanks in advance, Giancarlo ############################ ##

As I've mentioned here, before, I'm working on an extended version of mle(), a function from the stats4 package that's a wrapper for optim(). I'd like (against the advice of Peter Dalgaard -- sorry) to incorporate a "data" argument, similar to the arguments in lm, nls, nlme, etc., that would allow the log-likelihood function to be evaluated with different sets of data.

I'm trying to figure out the best way of fitting the same negative log-likelihood function to more than one set of data, using mle() from the stats4 package. Here's what I would have thought would work: -------------- library(stats4) ## simulate values r = rnorm(1000,mean=2) ## very basic neg. log likelihood function mll <- function(mu,logsigma) {

Hi there, When I do bootstrap on a maximum likelihood estimation, I try the following code, however, I get error: Error in minuslogl(alpha = 0, beta = 0) : object "x" not found It seems that mle() only get data from workspace, other than the boot.fun(). My question is how to pass the data to mle() in my case. I really appreciated to any suggestions. Best wishes, Jinsong

Hi, I'm trying to use mars function in R to interpolate nonlinear multivariate functions. However, it seems that mars gives me a fit which uses only very few basis function and it underfits very badly. For example, I have tried the following code to test mars: require("mda") f <- function(x,y) { x^2-y^2 }; #f <- function(x,y) { x+2*y }; # Grid x <-

Hi, There is something I don't get with object of class "mle" returned by a function I wrote. More precisely it's about the behaviour of method "confint" and "profile" applied to these object. I've written a short function (see below) whose arguments are: 1) A univariate sample (arising from a gamma, log-normal or whatever). 2) A character string

[posted to R-devel, no discussion: resubmitting it as a bug, just so it gets logged appropriately] Sorry to report further difficulties with nls and profiling and constraints ... the problem this time (which I didn't check for in my last round of testing) is that the nls profiler doesn't seem to respect constraints that have been set when using the port algorithm. See test code

Sorry to report further difficulties with nls and profiling and constraints ... the problem this time (which I didn't check for in my last round of testing) is that the nls profiler doesn't seem to respect constraints that have been set when using the port algorithm. See test code below ... If I can I will try to hack the code, but I will probably start by redefining my function with

Full_Name: S?bastien Villemot Version: 2.4.0 OS: Debian testing Submission from: (NULL) (62.212.121.128) Hi, In the mle() function of the stats4 package, there is a bug in the ordering of the variables given in the 'start' argument. By just changing the order of the variables listed in the 'start' list (the initialization values), it is possible to obtain different estimation

Dear R users, I am new to R. I would like to find *maximum likelihood estimators for psi and alpha* based on the following *log likelihood function*, c is consumption data comprising 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))});

So, I've embarked on my threatened modifications to the mle subset of the stats4 package. Most of what I've done so far has *not* been adding the slick formula interface, but rather making it work properly and reasonably robustly with real mle problems -- especially ones involving reasonably complex fixed and default parameter sets. Some of what I've done breaks backward

my problem actually arised with fitting the data to the weibulldistribution, where it is hard to see, if the proposed parameterestimates make sense. data1:2743;4678;21427;6194;10286;1505;12811;2161;6853;2625;14542;694;11491; ?? ?? ?? ?? ?? 14924;28640;17097;2136;5308;3477;91301;11488;3860;64114;14334 how am I supposed to know what starting values i have to take? i get different

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

Hi All, I'm using 'tck' option to *reduce* the length of tick marks but it is not working, can anyone please tell me where I'm going wrong... require(graphics) require(grDevices) x <- seq(-10, 10, length= 30) y <- x f <- function(x,y) { r <- sqrt(x^2+y^2); 10 * sin(r)/r } z <- outer(x, y, f) z[is.na(z)] <- 1 # 'bg' works but 'tck' is not showing

Dear list members, I want to draw surfaces of Dirichlet distributions with different parameter settings. My code is the following: #<begin code> a1 <- a2 <- a3 <- 2 #a2 <- .5 #a3 <- .5 x1 <- x2 <- seq(0.01, .99, by=.01) f <- function(x1, x2){ term1 <- gamma(a1+a2+a3)/(gamma(a1)*gamma(a2)*gamma(a3)) term2 <- x1^(a1-1)*x2^(a2-1)*(1-x1-x2)^(a3-1)

Dear all, I would like to put two perspective plots into one plot. The help page for ?persp shows how one can add points and lines but not another perspective plot. data(volcano) z <- 2 * volcano # Exaggerate the relief x <- 10 * (1:nrow(z)) # 10 meter spacing (S to N) y <- 10 * (1:ncol(z)) # 10 meter spacing (E to W) ## Don't draw the grid lines : border = NA persp(x,

Hi the list, I write a short function to draw lines in 3D, showing then turning. At some point, I add "delais" to slow down the rotation. So two questions: 1) I try to find a library to draw animate lines in 3D but I did not find. That surprise me since it is very simple to do. Did I forget to look somewhere ? If it does not exists and I have to use my own function : 2) Is it

I have an issue using mle in versions of 32 bits. I am writing a package which I want to submit to the CRAN. When doing the check, there is an example that has an error running in the 32 bits version. The problem comes from the mle function, using it with a lower constrain. In 64 bits version it works fine but when I put it in the R 32 bits it fails. (same numbers, all equal!) The call is: