similar to: Estimating parameters for a bimodal distribution

In S-Plus, there is a function ms() [minimum sums] that estimates parameters in a multivariate model and returns, along with the estimates, a loglikelihood score. It's very handy, but I have not found an R version yet. Does anyone know if such a thing exists? Thanks. Cheers, George ================================================================== George W. Gilchrist

Does anyone have an idea of how one might plot male and female symbols on a graph using R? Thanks! .................................................................. George W. Gilchrist Email #1: gwgilc at wm.edu Department of Biology, Box 8795 Email #2: kitesci at cox.net College of William & Mary Phone: (757) 221-7751 Williamsburg, VA

I am trying to do a series of xyplots plots, using a "for" loop to substitute the appropriate variables for each plot. The basic command works fine by itself and produces a nice plot: > i<-3 > trellis.device(theme="col.whitebg") > xyplot(as.formula(paste(tmp00[2*i], "~ ", tmp00[(2*i)-1], +

In S-Plus, I can obtain polynomial contrasts for an ordered factor with contr.poly(). The function also exists in R, however is limited to factors where the levels are equally spaced. In S-Plus, one can obtain the contrasts for a set of numeric values representing unequally spaced ordered factors. Has anyone implemented this in R? I see that the S-Plus function calls another function (poly.raw())

I have a very large dataframe and wish to extract a subset of rows. I have a two column matrix listing the starting and ending indices of one subset on each row. My idea is to create a vector of indices that could be applied to the dataframe and I have a solution using a for loop (below). But surely there is some more elegant way to do this! I looked thorough the archives without

I need to extract the degrees of freedom and log likelihoods from a series of mixed models computed using lmer/lme4. If I ask for logLik (lmer.object), I get something like > logLik(lmer.object) 'log Lik.' -177.1000 (df=10) Can I easily get that df from there (or elsewhere) into an object? Thank you for any ideas. George

Hi there The default option for saving graphics from R (1.9.1) on my Mac is as a pdf file. If I open the file in Acrobat reader it looks really good and crisp, and is obviously saved as vector graphics, since I can zoom in as much as I like and it continues to look really nice. If I import it into MS Word (from office 2000), or Textedit, however, it imports it as a bitmap and unless I save

I'm trying to learn statistics and R at the same time. I have an undergraduate science degree and one year of calculus (30 years ago), but never took a stats course. I hope to take some stats courses in the next year, but thought I would start to see how much I could teach myself. I work for an organization that analyses behavior change communication programs regarding HIV/AIDS and

I've been experimenting with drop1 for my biostatistics class, to obtain the so-called Type III sums of squares. I am fully aware of the deficiencies of this method, however I feel that the students should be familiar with it. What I find baffling is that when applied to a fully balanced design, you obtain different sums of squares. I've used this for several years in Splus and R and never

My apologies to the list for sending this without adequate research. I have found my answer; please ignore! Thanks. I've been experimenting with drop1 for my biostatistics class, to obtain the so-called Type III sums of squares. I am fully aware of the deficiencies of this method, however I feel that the students should be familiar with it. What I find baffling is that when applied to a fully

Full_Name: George W. Gilchrist Version: 1.6.2 OS: OS X Submission from: (NULL) (128.239.124.126) Start with a tab-delimited or comma-delimited text file created on the Mac and use read.table("filename.txt", header=T) to read it in. When the first column of the file contains a character vector, and there is a header line, the first letter of the first column of the fifth row is appended

Hello everybody, I need to setup a Domain/subdomain environment with Windows AD. All the DCs run Windows Server 2012 R2. All domains (root and subdomains) The forest and domain functional level are set to Windows 2008 R2. I want to use Samba 4 server as fileservers in these domains, but up to now I have trouble adding Samba 4 member servers to Windows AD. My test environment is made of 2

Dear all: Assume I have 3 distributions, x1, x2, and x3. x1 ~ normal(mu1, sd1) x2 ~ normal(mu2, sd2) x3 ~ normal(mu3, sd3) y1 = x1 + x2 y2 = x1 + x3 Now that the data I can observed is only y1 and y2. It is easy to estimate (mu1+m2), (mu1+mu3), (sd1^2+sd2^2) and (sd1^2+sd3^2) by EM algorithm since y1 ~ normal(mu1+mu2, sqrt(sd1^2+sd2^2)) and y2 ~ normal(mu1+mu3, sqrt(sd1^2+sd3^2)) However, I want

Windows 7, R 2.12.1 Colleagues, I am trying to understand the n.for.2means function. The code below is a copy of the function (renamed to n.for.2means.js). I have inserted a single line of code towards the bottom of the function which uses the cat function to print the value of n1. You will note the value (preceded by stars) is printed as 1. The function (1) prints a lot of output without any

Hi, I''m running Opensolaris 2009.06, and I''m facing a serious performance loss with ZFS ! It''s a raidz1 pool, made of 4 x 1TB SATA disks : zfs_raid ONLINE 0 0 0 raidz1 ONLINE 0 0 0 c7t2d0 ONLINE 0 0 0 c7t3d0 ONLINE 0 0 0 c7t4d0 ONLINE 0 0

Dear R helpers I have following data stocks <- c("ABC", "DEF", "GHI", "JKL") prices_df <- data.frame(ABC = c(17,24,15,22,16,22,17,22,15,19),                                          DEF = c(22,28,20,20,28,26,29,18,24,21),                                           GHI = c(32,27,32,36,37,37,34,23,25,32),                                          

Hi, I already found a conversation on the integration of a normal distribution and two suggested solutions (https://stat.ethz.ch/pipermail/r-help/2007-January/124008.html): 1) integrate(dnorm, 0,1, mean = 0, sd = 1.2) and 2) pnorm(1, mean = 0, sd = 1.2) - pnorm(0, mean = 0, sd = 1.2) where the pnorm-approach is supposed to be faster and with higher precision. I want to integrate a mixed

hello, I would like to create the following barplot: I have 4 different data sets (same length + stddev for each data point) data1 sd1 data2 sd2 data3 sd3 data4 sd4 now, I'd like to plot in the following way: data1[1],data2[1],data3[1],data4[1] with it's sd-values side-by-side at one x-axis label (named "position 1") and each bar in different colors.

Dear List: I am running into a memory issue that I haven't noticed before. I am running a simulation with all of the code used below. I have increased my memory to 712mb and have a total of 1 gb on my machine. What appears to be happening is I run a simulation where I create 1,000 datasets with a sample size of 100. I then run each dataset through a gls and obtain some estimates. This works

Hi all, I appreciate the help this list has given me before. I have a question which has been perplexing me. I have been working on doing a Bayesian calculating inserting studies sequentially after using a non-informative prior to get a meta-analysis type result. I created a function using three iterations of this, my code is below. I insert prior mean and precision (I add precision manually