similar to: Missing data and Imputation

Greetings folks, Shafer's S-plus package "norm" for multiple imputation of missing values in multivariate normal data has been most kindly and usefully ported to R by Alvaro A. Novo. Shafer's website http://www.stat.psu.edu/~jls/ lists four S-plus packages in all: NORM - multiple imputation of multivariate continuous data CAT - multiple imputation of multivariate

Hi Folks, Sorry to raise what has probably been discussed before, but I an repeatedly struck by the comparative slowness of S-plus for Windows compared with R for Linux when doing much the same thing. I don't have a direct comparison, because they're not running on the same machine; but machine W has a faster CPU and more RAM than machine L, yet S-plus on W seems to take longer by quite

What R functionnalities are there to do missing values imputation (substantial proportion of missing data)? I would prefer to use maximum likelihood methods ; is the EM algorithm implemented? in which package? Thanks Anne ---------------------------------------------------- Anne Piotet Tel: +41 79 359 83 32 (mobile) Email: anne.piotet@m-td.com

Hi Folks, I see that people have been discussing the win.metafile device on the list since before 2000. Yet I have never seen this on a Linux distribution of R. Is this because the device works by making calls (GPL calls of course!) to a proprietary Windows library? In that case I can understand that it would be far from kosher to implement it on Linux. But I'd like confirmation. I must

Hi I am trying to impute missing values for my data.frame. As I intend to use the complete data for prediction I am currently measuring the success of an imputation method by its resulting classification error in my training data. I have tried several approaches to replace missing values: - mean/median substitution - substitution by a value selected from the observed values of a variable - MLE

In some languages there is a function gensym() which returns a new unique name (in the current environment). This is quite helpful when one has to do temporary assignments. I could not find such a function in R. Is there one? -- Erich Neuwirth, Computer Supported Didactics Working Group Visit our SunSITE at http://sunsite.univie.ac.at Phone: +43-1-4277-38624 Fax: +43-1-4277-9386

I am desperately trying to impute missing data using 'imp.mix' but always run into this yucky error message to which I cannot find the solution. It's the first time I am using mix and I'm trying really hard to understand, but there's just this one step I don't get...perhaps someone knows the answer? Thanks! Jens My code runs:

Dear all! I'd like to do multiple imputation of missing values with s-plus libraries that are provided by Shafer (http://www.stat.psu.edu/~jls/misoftwa.html). I wonder, whether these libraries are compatible or somehow convertible to R (because I don't have S-plus), so that I can use this functions using the R Program. I would be happy if you could tell me, -if it is possible to use

Hi In a dataset I have length and age for cod. The age, however, is ony given for 40-100% of the fish. What I need to do is to fill inn the NAs in a correct way, so that age has a value for each length. This is to be done for each sample seperately (there are 324 samples), meaning the NAs for sampleno 1 shall be calculated from the known values from sampleno 1. As for example length 55 cm

As a user of only R, I don't use much of the potential of ESS and Emacs. Without entering a religious feud, is there any reason I should use XEmacs rather than my current GNU Emacs? (I looked on the XEmacs site, but I didn't understand the programming issues they were talking about (over my head).) Martin Henry H. Stevens, Assistant Professor 338 Pearson Hall Botany Department Miami

Hi Folks, I'm using the 'norm' package (based on Shafer's NORM) on some data. In outline, (X,Y) are bivariate normal, var(X)=0.29, var(Y)=24.4, cov(X,Y)=-0.277, there are some 900 cases, and some 170 values of Y have been set "missing" (NA). The puzzle is that, repeating the multiple imputation starting from the same random seed, I get different answers from the repeats

Dear All, Is it possible to manage a svd analysis within a matrix containing NA values. If not how do I could overcome this problem. Thanks in advance Antonio

Here is a problem that perhaps someone out here has an idea about. It vaguely reminds me of something I've seen before, but can't place. Can anyone help? For multiple imputation, there are simpler methods available if the patterns of missing data are 'monotone' --- if Vj is missing then all variables Vk, k>j are also missing, vs. more complex methods required when the

Dear R-help, I am trying to impute missing data for the first time using R. The norm package seems to work for me, but the missing values that it returns seem odd at times -- for example it returns negative values for a variable that should only be positive. Does this matter in data analysis, and/or is there a way to limit the imputed values to be within the minimum and maximum of the actual

Dear alltogether, I experience very strange behavior of imputation of NA's with the NORM library. I use R 2.2.0, win32. The code is below and the same dataset was also tried with MICE and aregImpute() from HMISC _without_ any problem. The problem is as follows: (1) using the whole dataset results in very strange imputations - values far beyond the maximum of the respective column, >

Is anyone aware of a mechanism by which I could execute an R function from within java (say a servlet). thanks Richard Piper -- Intensive Care Unit, RNS Hospital, Sydney. Phone: 612-9926-8656 or 8617 FAX: 612-9439-8418 Page: 612-9962-4936 -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html

I've been doing some prototype simulations in Python, and my plan at first was to pass the results off to R, but now I would like to make more of an integrated use of the R routines. I'm curious about the use of libR.so, but I'm uncertain, still after having looked through the documentation 'Embedding R in Other Applications' and 'Writing R extensions' how I can

Suppose one wanted to build an R wizard for packaging... One would need to specify and create: package-name/ package-name/Description package-name/INDEX package-name/R/ package-name/man/ package-name/src/ >From this, we'd "probably" like to: - script-up the Description - provide a script for regenerating INDEX by calling out to the

> From: rossini@blindglobe.net (A.J. Rossini) > Date: 01 Nov 2000 07:47:21 -0800 [...] > Thanks for the pointer to stack/unstack -- now, having been reminded, > I think I'd seen these float through on the list (still doesn't solve > the missing modeling routines (parametric GLMMs, some of the > econometrics stuff -- does R _easily_ do 3SLS?), but they'll appear >

First let me confess that I am a R-novice. I am trying to fit a beta distribution for a dataset using fitdistr(MASS). I am having difficulties with it because the function tends to fit a distribution with a range of 0 to 1 (I guess). However, my dataset is not! Anytips or tricks will be very much appreciated. Many Thanks. T. S. Ramanarayanan, Ph.D. Aventis CropScience Research Triangle Park,