similar to: How to use MLE-class?

Dear Helpers: I'm trying to use packages "maps" and "mapdata" (see blow) to display the research resutls on map (Mid-Atlantic region). In particular, I need to mark a number of points in the map by giving their latitude and longitude information. For instance, I would like to mark a point on (long, lat) =(75.56027, 39.09271). Also, I need to mark several cities that I

Dear R folks: I wonder anyone has a elegent way of doing what I need to do. I have a data frame called with four columns: V1, V2, A1 and A2: V1 V2 A1 A2 A B 1.2 2.0 A D 1.2 4.0 A C 2.4 2.2 What I need to do is to convert it into the following data frame with a new column x, where x is just the stacked up of A1 and A2 placed with respective V1 and V2 in the first two

Dear R users: My question is how to write output in a specific formate with irregular spacing? Say that I have the following DF with three columns (A-C): A B C a10 100.0 212 The objective is to write an output file such that column A occupies 1-10 spaces aligned to the left, column B occupies 11-15 spaces aligned to the right, and finally column C takes 16-25 spaces

Dear R users: I'm trying to generate a output file with fixed format using function "sprintf" in R. However, the execution time in R is very long even the toy data (smaller size df) seems to work fine. The syntax that I used is as follows: df.fmt <- sprintf("%2s%2s%2.4f", df$v1, df$v2, df$v3) write.table(df.fmt, output.name,...) The actual dataset is a df with the

Hi, I am a user of R computer language.Several days ago,I download R-2.1.0.From the help manual,I saw there is a function "mle" to find the maximum likelihood estimators.But when I try to use this function,there is no this function.Could you help me to solve this problem? I am looking forward to your answer. Thank you. Jun Liu

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

Hi I hope this is the right forum - if not, point me please to a better one. I am using R 2.3.0 on Linux, SuSE 10. I have a question concerning mle (method="BFGS"). I have a few models which I am fitting to existing data points. I realised, that the likelihood is quite sensitive to the start values for one parameter. I am wondering: what is the best approach to identify the right

Dear R users, I am writing to you because I have a few question on how to fix the error term variances in lme in the hope that you could help me. To my knowledge, the closest possibility is to fix the var-cov structure, but not the whole var-cov matrix. I found an old thread (a few years ago) about this, and it seems that the only alternative is to write the likelihood down and use optim or a

Hi everyone! I am using the mle {stats4} to estimate the parameters of distributions by MLE method. I have a problem with the examples they provided with the mle{stats4} html files. Please check the example and my question below! *Here is the mle html help file * http://stat.ethz.ch/R-manual/R-devel/library/stats4/html/mle.html http://stat.ethz.ch/R-manual/R-devel/library/stats4/html/mle.html

Hi, How can we set the environment for the minuslog function in mle()? The call in this code fails because the "ll" function cannot find the object 'y'. Modifying from the example in ?mle: library(stats4) ll <- function(ymax=15, xhalf=6) { -sum(stats::dpois(y, lambda=ymax/(1+x/xhalf), log=TRUE)) } fit.mle <- function(FUN, x, y) { loglik.fun <- match.fun(FUN)

I learned R & MLE in the last few days. It is great! I wrote up my explorations as http://www.mayin.org/ajayshah/KB/R/mle/mle.html I will be most happy if R gurus will look at this and comment on how it can be improved. I have a few specific questions: * Should one use optim() or should one use stats4::mle()? I felt that mle() wasn't adding much value compared with optim, and

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, I am looking for some help regarding the use of the mle function. I am trying to get mle for 3 parameters (theta0, theta1 and theta2) that have been defined in the the log-likelihood equation as theta0=theta[1], theta1=theta[2] and theta2=theta[3]. My R code for mle is: mle(Poisson.lik, start=list(theta=c(20,1,1), method="Nelder-Mead", fixed=list(w=w, t1=t1, t2=t2)) But I keep

R 2.3.0, all packages up to date Linux, SuSE 10.0 Hi I want to calculate AIC or BIC from several results from mle calculation. I found the AIC function, but it does not seem to work with objects of class mle - If I execute the following: ml1 <- mle(...) AIC(ml1) I get the following error messale: Error in logLik(object) : no applicable method for "logLik" Therefore I am using the

I made one typo in my previous mail.   May I ask one statistics related question please? I have one query on MLE itself. It's property says that, for large sample size it is normally distributed [i.e. asymptotically normal]. On the other hand it is "Consistent" as well. My doubt is, how this two asymptotic properties exist simultaneously? If it is consistent then asymptotically it

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 stats4::mle -- a spurious error saying that a better fit has been

Hi the list, I am experiencing several issues with profile.mle (and consequently with confint.mle) (stat4 version 2.9.2), and I have to spend a lot of time to find workarounds to what looks like interface bugs. I would be glad to get feedback from experienced users to know if I am really asking too much or if there is room for improvement. * Problem #1 with fixed parameters. I can't

Hi the list, I would need some advice on something that looks like a FAQ: the possibility of providing vectors to optim() function. Here is a stupid and short example summarizing the problem: -------------------------------- example 1 ------------ 8< ---------------------- library(stats4) data <- rnorm(100,0,1) lik1 <- function(m, v, data) { N <- length(data) lik.mean <-

Dear All, There are two things about mle() that I wasn't so sure. 1) can mle() handle vector based parameter? say ll<-function(theta=rep(1,20)){..............} I tried such function, it worked for "optim" but not for "mle". 2) is there a general suggestion for the maximum number of parameters allowed to use in mle() or optim()? Thank you. Regards, MJO

Dear R-Users, I am trying to use mle() to optimize two (or more) parameters, but I want to specify those parmeters in a data frame rather than having to spell them out separately in the "start" variable of mle(). My call is > mle(negll, start=list(aps=init), fixed=list(measphot=newphot, formod=formod, Nbands=Nbands), method="BFGS") where negll is a function I have