similar to: find "CP"

Hello, I have a question pertaining to the stepwise regression which I am trying to perform. I have a data set in which I have 14 predictor variables accompanying my response variable. I am not sure what the difference is between the function "mle.stepwise" found in the wle package and the functions "step" or "stepAIC"? When would one use

Folks, I'm kind of newbie in R, but with some background in Matlab and VBA programming. Last month I was implementing a Maximum Likelihood Estimation in Matlab, but the algorithms didn't converge. So my academic advisor suggested using R. My problem is: estimate a mean reverting jump diffusion parameters. I've succeeded in deriving the likelihood function (which looks like a gaussian

Hi, all When I am using mle.cv(wle), I find a interesting problem: I can't do leave-one-out cross-validation with mle.cv(wle). I will illustrate the problem as following: > xx=matrix(rnorm(20*3),ncol=3) > bb=c(1,2,0) > yy=xx%*%bb+rnorm(20,0,0.001)+0 > summary(mle.cv(yy~xx,split=nrow(xx)-1,monte.carlo=2*nrow(xx),verbose=T), num.max=1)[[1]] mle.cv: dimension of the split subsample

Hi! I need to fit a data that shows up as two gaussians partially superimposed to the corresponding gaussian distributions, i.e. data=c(rnorm(100,5,2),rnorm(100,-6,1)) I figured it out how to do it with mle or fitdistr when only one gaussian is necessary, but not with two or more. Is there a function in R to do this? Thank you very much in advance, Luis

I know this a newbie question, but I've only just started using AIC for model comparison and after a bunch of different keyword searches I've failed to find a page laying out what the differences are between the AIC scores assigned by AIC() and mle.aic() using default settings. I started by using mle.aic() to find the best submodels, but then I wanted to also be able to make comparisons

Subject: Eliminate repeated components from a vector X-Mailer: VM 7.00 under 21.4 (patch 6) "Common Lisp" XEmacs Lucid Reply-To: fjmolina at lbl.gov FCC: /home/f/.xemacs/mail/sent Does anyone know how I can eliminate repeated elements from a vector?

Here's a more general question following up on the specific question I asked earlier: Can anybody recommend an R command other than mle.aic() (from the wle package) that will give back a ranked list of submodels? It seems like a pretty basic piece of functionality, but the closest I've been able to find is stepAIC(), which as far as I can tell only gives back the best submodel, not a

Hi, I have the response variable 'Y' and four predictors say X1, X2, X3 and X4. Assuming all the assmptions like Y follows normal distribution etc. hold and I want to run linear multiple regression. How do I run the stepwise regression (forward as well as the backward regression). >From other software (i.e. minitab), I know only X1 and X2 are significant so my regression equation

Hi ALL, Short description of my problem: I am not able to make wireless network working on the IBM ThinkPad T43p. System: T43p OS: CentOS 4.4 kernel: 2.6.9-34.EL firmware: ipw2200-firmware-3.0-3.nodist.rf.noarch.rpm What did I do ? - installed firmware from RPM package - removed kernel driver (/sbin/rmmod ipw2200) - installed kernel module (/sbin/modprobe ipw2200) dmesg output:

Hi, today I updated the glibc packages on some CentOS machines. After the Update I checked which services/processes I have to restart "yum -C ps" or "needs-restarting" At the most machines I get no information about necessary restarts, but at two machines a long listing : 1 : /sbin/init 386 : /sbin/udevd-d 659 : /sbin/udevd-d 999 : /usr/sbin/vmtoolsd 1103 : auditd 1128 :

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

>Y [,1] [,2] [,3] [1,] 0 1 0 [2,] 0 1 0 [3,] 0 0 1 [4,] 1 0 0 [5,] 0 0 1 [6,] 0 0 1 [7,] 1 0 0 [8,] 1 0 0 [9,] 0 0 1 [10,] 1 0 0 >X pri82 pan82 1 0 0 2 0 0 3 1 0 4 1 0 5 0 1 6 0 0 7 1 0 8 1 0 9 0 0 10

hello my data is data2:2743 4678 21427 6194 10286 1505 12811 2161 6853 2625 14542 694 11491 14924 28640 17097 2136 5308 3477 91301 11488 3860 64114 14334 by calculating shape<-(mean(data2))^2/var(data2) scale<-var(data2)/mean(data2) i get the idea what the parameters of the gammadistribution would be. but if i try using the method mle() i get stock and i don't know, how to

Hello everyone, I'm trying to use mle from package stats4 to fit a bi/multi-modal distribution to some data, but I have some problems with it. Here's what I'm doing (for a bimodal distribution): # Build some fake binormally distributed data, the procedure fails also with real data, so the problem isn't here data = c(rnorm(1000, 3, 0.5), rnorm(500, 5, 0.3)) # Just to check

Hi everyone: I have a density function f(x|theta)=theta*x^(theta-1),where 0<x<1,0<theta<infinite I want to pratice on R to find the MLE of this function,here is my code: x <- (0:10)/10 f<-function(theta) prod(theta*x^(theta-1)) mle(f) and r gave me :Error in eval(expr, envir, enclos) : argument is missing, with no default what mistake I just made?and how to add a

Dear R-helpers, I was wondering if anyone has or knows someone who might have an implementation of algorithm for estimating SETAR models including the lag-order. For some reason my code gives me a bit wrong results. I am fighting with it for a week and cannot bring it down. Thanks a million in advance, Sincerely, Evgueni McGill University Department of Economics

Hi all, Could anybody point me to a good/robust numerical optimization program to use in R? I am doing some MLE fitting. Thanks!

No manpage or other info in the system about the hald or hal. What little I did find on a RH site did not really enlighten me that much. Is there some obscure documentation somewhere about the hald and its assets and attributes? -- Snowman

Hello R users, I have three questions and I would be grateful if someone could give me an answer to each of these. 1) I have constracted a function that returns an output, which runs in a while( condition ){ run function } loop. I would like to know if there is a way to get the outputs in different windows, every time the function runs, so as to compare easier the results. 2) In my

some notes: - for this kind of discussion, please cc upsdev list (I've added it), - I've fwded the full thread to upsdev, - this subject is part of what I call NUT-NG (next gen.), aka nut 3.0... - I'll study in depth the thread this week end, and complete with my thoughts, - thanks to Stan to have put us all in touch Arnaud 2006/3/10, Stanislav Brabec <sbrabec@suse.cz>: >