similar to: lda and maximum likelihood

Dear all, I am trying to model variation of distribution of species assemblages according to environmental variables. For that I use a log linear multinomial regression. In order to select variables that mostly discriminate the assemblages, I tried to apply a hierarchical partitioning protocol to my data set. For that I have adapted the all.regs() for multinomial model. The problem is that I

Dear List: Is any one aware of a package that would extend the D() function and allow for one to maximize a likelihood function symbolically? Something akin to Solve[x==0, parameter] function in Mathematica? Clearly R has the capacity to _compute_ MLEs given a set of data. But, I'm looking for a package that would allow for me to define the likelihood function, find the 1st order partial

I am trying to figure out how to run maximum likelihood in R. Here is my situation: I have the following equation: equation<-(1/LR-(exp(-k*T)*LM)*(1-exp(-k))) LR, T, and LM are vectors of data. I want to R to change the value of k to maximize the value of equation. My attempts at optim and optimize have been unsuccessful. Are these the recommended functions that I should use to maximize

I forgot to add that I first gave a starting value for K. Nonlinear least squares won't work because my errors are not normally distributed. Any advide on my maximum likelihood function would be greatly appreciated. ---------------------------- Original Message ---------------------------- Subject: RE: [R] maximum likelihood problem From: "Ravi Varadhan" <rvaradhan at

Dear mailing list, I would like to use the optim() command in order to maximize the logged likelihood of the following function, where p is the parameter of interest and should be constrained between 0 and positive infinity. y = 1/2 * ((te - x)/(te - tc))^p x and y are given by x <- c(5.18, 6.28, 7.00, 7.08, 7.54, 7.90, 8.24, 8.64, 12.17, 12.89, 14.27, 15.38, 15.80, 16.46, 20.41, 21.27,

We want to compute a pseudo R-squared for a model whose parameter estimation was based on maximum likelihood (function likfit, package geoR). I tried to compute the R2 proposed by Maddala (1983) which compare the maximized likelihood for the model without any predictor and the maximized likelihood for the model with all predictors. I got a really low value (0,01%). Did I miss something? Are

Dear R users and developpers, My question is adressed to both of you, so I choose R-help to post it. Are there any plans to jazz up the main R website : http://www.r-project.org The look it have now is the same for a long time and kind of sad compared to other statistical package's website. Of course, the comparison is not fair, since companies are paying web designers to draw lollipop

Dear R users, I am a mathematics postdoc at UC Berkeley. I have written a package in a Computational Algebra System named Singular http://www.singular.uni-kl.de to compute the Maximum Likelihood of a given probability distribution over several discrete random variables. This package gives exact answers to the problem. But more importantly, it gives All MLE solutions. My understanding is that

Hello, My name is Vincent and I have some difficulties to realize my project. Indeed, I must developp a streaming flac client/server and I have some difficulties to find detailed information about this. I chose to use the platform Ices/Icecast to do my project. I took the Vorbis streaming like example but the library has not the same structure as the flac library. So , I send this message in

Hello Amelie, I don't have an answer to your question, but I just wanted to point out this page I noticed recently ( http://hlplab.wordpress.com/2009/05/07/multinomial-random-effects-models-in-r/), which might be helpful. I'm also interested in figuring out how to do a multinomial glmm, so if you find out anything I'd be happy to hear more about it! Based on what I've found so

Hi! Recently I try to find the method maximum likelihood for gamma,weibull,Pearson type III,Kappa Distribution, mixed exponential distribution, skew distribution. I have tried function ms() for gamma two parameters and weibull two parameters.It works but not for Pearson type III. I have problem to find the likelihood function for mixed exponential distribution and kappa distribution. So can

Hi, I want to use Maximum likelihood to estimate the parameters from my regression line. I have purchased the book "Applied linear statistical models" from Neter, Kutner, nachtsheim & Wasserman, and in one of the first chapters, they use maximum likelihood to estimate the parameters. Now I want to tried it for my self, but couldn't find the right function. In the book, they give

Hi R-experts, There is lots of information about maximum likelihood estimation in R. However, I didn't came across anything about maximum likelihood with constraints. For example, estimation of parameters k(1) to k(20) with maximum likelihood, where sum(k(i)) = 0. Is there any standard function in R that can do this, or is this something that I should set up myself? Greetings, Church

I want to find ML estimates of a model using mle2 in bbmle package. When I insert new parameters (for new covariates) in model the log-likelihood value does not change and the estimated value is exactly the initial value that I determined. What's the problem? This is the code and the result: As you see the estimated values for b2 , b3 and b4 are the initial values of them. The

Hi guys again, it seems I haven't been doing the maximum likelihood estimation correctly. I quote below, can someone explain to me please what does it mean that the 2nd and 3rd derivatives of the function equals zero and how to compute that in R. "We have our initial estimated, subjective parameters for the gamma mixture and we have our likelihood that is the mixture of negative

Hello all, I'm trying to calculate the Maximum likelihood of individuals to get the ancestry. I mixd 3 populations 15 generations in proportion of 20% 20% 60% when each population sorce have diferent genome (0 1 and 2) with frequencies for each one. So now i have individuals looks like 0 0 2 1 1 2 0 ..... and i don't now how to calculate the mle although i try to figure out from the

I'm trying to get a grasp of maximum-likelihood estimation and would like to find a package that performs mle (hopefully a simple example). It seems as if there are plenty of packages that make use of different types of likelihood estimators, but none are of a simple, "newbie" type. Does anyone have a suggestion for which package would be the best for a mle example? Thanks, Jeff.

Hello, I'm trying to calculate the Maximum likelihood estimators for a dataset which contains censored data. I started by using the function "nlm", but isn't there a separate method for doing this for e.g. the "weibull" and the "log-normal" distribution? Thanks, Olivia [[alternative HTML version deleted]]

Have a look at ?optim. I don't think it has the BHHH algorithm as an option, though. =========================================== David Barron Jesus College University of Oxford -----Original Message----- From: r-help-bounces at stat.math.ethz.ch [mailto:r-help-bounces at stat.math.ethz.ch]On Behalf Of Harold Doran Sent: 10 July 2003 15:43 To: Fohr, Marc [AM]; R-help at stat.math.ethz.ch

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