similar to: mixture of 2 normals - starting values

Hi there. I was wondering if somebody knows how to perform a bagging procedure on a classification tree without running the classifier with weights. Let me first explain why I need this and then give some details of what I have found out so far. I am thinking about implementing the bagging procedure in Matlab. Matlab has a simple classification tree function (in their Statistics toolbox) but

Hello! I would like to know how do I citate R? I have used it during my Master thesis but I don’t know how to citate during the text and on the references. I’ve looked for it on the web page but only found how to citate the FAQ. Thank you in advance. Tatiana Fernandes Universidade Estadual do Norte Fluminense Laboratório de Ciências Ambientais - CBB Av. Alberto Lamego, 2.000 - Campos dos

Hi, Is there any package that I can use to simulate the Gaussian Mixture Model , which is a mixture modeling method that is widely used in statistical learning theory. I know there is a mclust, however, I think it is a little bit different from my problem. Thanks very much.. regards. -------------------------- Peng Jiang ?? Ph.D. Candidate Antai College of Economics &

I just ran into this strange behavior. y <- rnorm(1000) x <- seq(0, length=length(y)) plot(x, y, type='l', lty=1) - instantaneous plot(x, y, type='l', lty=2) - 18s plotting lines + 15s plotting axes = 33s plot(x, y, type='l', lty=3) - 76s ,, + 75s ,, = 151s plot(x, y, type='l', lty=4) -

Hello, I want to understand how to tell if a model is significant. For example I have vectX1 and vectY1. I seek first what model is best suited for my vectors and then I want to know if my result is significant. I'am doing like this: model1 <- lm(vectY1 ~ vectX1, data= d), model2 <- nls(vectY1 ~ a*(1-exp(-vectX1/b)) + c, data= d, start = list(a=1, b=3, c=0)) aic1 <- AIC(model1)

hi i'm looking for a gibbs sampling algorithm for R for the case of mixture of K normals, and in particular for the case of bivariate normals. i'd be grateful if anyone could send its own R-routine, at least for the univariate case. thank you in advance matteo

Hello, I am trying to find out if R can do the following: I have a mixture of normals say f = 0.2*Normal(2, 5) + 0.8*Normal(3,2) How do I find the difference in the densities at any particular point of f and at Normal(2,5)? -- Thanks, Jim. [[alternative HTML version deleted]]

I couldn't find a direct answer in CRAN to this question, so I'm asking with some trepidation. I have a multivariate dataset (data.frame) with columns that can be expressed as a set of mixed normals (at least I think) and need to impute values that have constraints (truncated mixture of normals where the values cannot be below zero). If there isn't a package that can do this, is there

Hi all I found the Camping page on Wikipedia in need of some serious TLC, so I updated it, added some newer links and removed the ''stub'' status: http://en.wikipedia.org/wiki/Camping_%28microframework%29 I also pointed people to the Github repo for version 1.9. Please take a look and either make suggestions for further material for me to add (not too much...

Dear All, I wonder if there is an R package to estimate the generalized linear mixed models but with a random effects having a mixture of normals as a prior distributinon .. Thank you, Abderrahim [[alternative HTML version deleted]]

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Dear Friends, Is there an R package which implements regression models with error distributions following a scale mixture of normals? Thanks Anup

Hi, I would like to know if it is possible to have a "R code" to estimate the parameters of a mixture of bivariate (or multivariate) normals via EM Algorithm. I tried to write it, but in the estimation of the matrix of variance and covariance, i have some problems. I generate two bidimensional vectors both from different distribution with their own vector means and variance and

Can anyone send me the R code for fitting a mixture of normal distributions. Or in fact any'combination' of mixtures of distributions. I looke dta mix but it is still not clear to me. Jim [[alternative HTML version deleted]]

All: I am trying to fit a mixture of 2 normals with > 110 million observations. I am running R 2.5.1 on a box with 1gb RAM running 32-bit windows and I continue to run out of memory. Does anyone have any suggestions. Thanks so much, Tim [[alternative HTML version deleted]]

Is there any way to process the "vignette" documantation files? I have been looking at the bioconductor packages and most of them have *.Rnw files in doc directories. They look like regular TeX but have sections showing R code that seem to choke TeX. Thanks, Andy __________________________________ Andy Jaworski Engineering Systems Technology Center 3M Center, 518-1-01 St. Paul, MN

Hello- While I was reading a tutorial book for R (actually, for S-Plus:Brian S. Everitt. A Handbook of Statistical Analysis using S-PLUS. Chapman & Hall, London, 1994) I tried to execute this simple exercise: > x <- -c(1,2,3,4,5,6) > X <- -c(10,11,12,100,-5,-6) >x+X [1] -11, -13, -15, -104, 0, 0 As you can see, the added vectors resulted in

Dear members of the R-Help Team, we are reaching out to you with a question regarding using intervals()<https://www.rdocumentation.org/packages/nlme/versions/3.1-163/topics/intervals> to create inference for nlme()<https://www.rdocumentation.org/packages/nlme/versions/3.1-164/topics/nlme> function. The maintainer for the nlme package is listed as the R-Core Team and we were advised

I would like to buy a basic statistics book (experimental design, sampling, ANOVA, regression, etc.) with examples in R. Or download it in PDF or html format. I went to the CRAN contributed documentation, but there were only R textbooks, that is, textbooks where R is the focus, not the statistics. And I would like to find the opposite. Other text I am trying to find is multivariate data

I think that there is a bug in the as.POSIXct function on Windows. Here is what I get on Win2000, Pentium III machine in R 1.8.1. > dd1 <- ISOdatetime(2003, 10, 26, 0, 59, 59) > dd2 <- ISOdatetime(2003, 10, 26, 1, 0, 0) > dd2 - dd1 Time difference of 1.000278 hours Now, the 26th of October was the day that change to the standard time occurred, so I suspect that this has