similar to: analyze subsample of dataframe

I am trying to build Miredo 1.1.5 (http://www.remlab.net/miredo/devel.shtml.en) I have followed the rpmbuild instructions from: http://www.owlriver.com/tips/non-root/, and have the miredo source in ~/build/miredo-1.1.5. I run ./configure (as the INSTALL text file tells me to do) and get the error: checking for Judy.h usablity... no checking for Judy.h presence... no checking for Judy.h...

Since upgrading my server from CentOS 4.5 to 4.6 I've been getting the following error from amanda backups: mutilate /home lev 1 FAILED [compress got signal 11, /bin/tar got signal 13] I was away from the house for most of the end of December and had a couple of other issues that came up that could have been related but apparently weren't (why is it that several things all go wrong

Hello. I know that it is recommended to run smbd as a standalone daemon and to avoid inetd. Can you please tell me why inetd is discouraged and what problems it imposes? Also, I have one user who is having problems accessing her personal files on a MacOSX 10.3.2 via smb. Any ideas what may be causing it? Judy Lin NACS-DCS

Dieter Menne pointed out that the (small) xml attachment didn't make it. Here is an in-line version (see end of message). Let's hope it works this time. I'm struggling with interpreting XML files created by ADODB as data.frames and I'm looking for advice. Note: This xlm contains a result set which comes from a rectangular data array. I've been trying to play with

I want to create a user "samba" that has admin privileges over the directory where Win95 apps will be installed, but does not have root privileges. Are their any problems with doing so? Thanks, Carey =====================================================================e <> Carey F. Cox, PhD | PHONE: (409) 880-8770 <> <> Assistant

Hi, I'm trying to write a code (see below) to randomly resample measurements of one variable (say here the variable "counts" in the data frame "dat") with different resampled subsample sizes. The code works fine for a single resampled subsample size (in the code below = 10). I then tried to generalize this by writing a function with a loop, where in each loop the function

I am using R-2.10.1 binary from CRAN on a WinXP Pro system. I also use SAS v9.2 on the same box. I just started using the SAS ODBC driver that comes with version 9 of SAS. I have been able to set up an ODBC source for SAS datasets using the driver, and then with RODBC I am able to read a sample SAS dataset. > library(RODBC) > ch <- odbcConnect('sasodbc', believeNRows=FALSE)

Hi all! I have an ordered vector of values. The distribution of these values can be modeled by a sum of Gaussians. So I'm using the package 'mclust' to get the Gaussians's parameters for this 1D distribution. It works very well, but, for input sizes above 100.000 values it starts taking really forever. Unfortunately my dataset has around 4.6M values... My question: is it

What is the size of the boostrapped subsample in ecodist mantel() thanks [[alternative HTML version deleted]]

I'm struggling with interpreting XML files created by ADODB as data.frames and I'm looking for advice (see attached example file). Note: This file contains a result set which comes from a rectangular data array. I've been trying to play with parameters to the xmlToDataFrame function in the XML package but I dont get it to extract the data frame. This is what the result should look

Hello, I'm most grateful for your time to read this. I have a uber size 30GB file of 6 million records and 3000 (mostly categorical data) columns in csv format. I want to bootstrap subsamples for multinomial regression, but it's proving difficult even with my 64GB RAM in my machine and twice that swap file , the process becomes super slow and halts. I'm thinking about generating

Hi All, I want to select rows at random from a large data.frame while achieving a particular distribution defined my a given subset of this data.frame. How can I do this? More details and what I've done so far is given below. I have gene expression data and gene sets of interest. In order to look at enrichment of differential expression I'm doing a simple permutation approach: Selecting

Dear R-help, First of all, thank you VERY much for any help you have time to offer. I greatly appreciate it. I would like to write a function that, given an arbitrary number of factors from a data frame, tabulates the number of occurrences of each unique combination of the factors. Cleary, this works: > table(horse,date,surface) <SNIP> , , surface = TURF

I suspect I'm looking in the wrong places, so guidance to the relevant documentation would be as welcome as a little code snippet. I have time series data stored in a MySQL database. There is the usual DATE field, along with a double precision number: there are daily values (including only normal working days: Monday through Friday). I actually have to do a couple things here. Because of

Dear Mailing List I have a data set (data4) consisting of a number of factors and a response variable. I wish to randomly sample from a combination of two of those factors (GIS_station and Distance_code2) and return a new dataframe containing the original data structure (i.e. all the columns) but only containing the randomly selected rows. The number of rows in each combination of GIS_station

-----BEGIN PGP SIGNED MESSAGE----- hello, all! [metainfo: i'm using redhat linux 5.0, and have tried both the rpm that came with redhat and 1.9.18p7-50.1 from the samba website.] i can't seem to get smbmount to mount a share and give the files in the mountpoint group ownership of anything but root. the version of the man page on the samba website says you can

hello there, Is there a way of truncating in the opposite direction so as to retain only the values to the right of the decimal?? i.e. rather than: > trunc(39.5) [1] 39 i would get something like: > revtrunc(39.5) [1] 0.5 I've been searching to no avail but I imagine there is a very simple solution! Tyler -- View this message in context:

For personal aesthetic reasons, I changed the name "data" to "dat". Your code, with a slight modification: set.seed (1357) ## for reproducibility dat <- data.frame(var1=seq(1:40), var2=seq(40,1)) dat$sampleNo <- 0 idx <- sample(seq(1,nrow(dat)), size=10, replace=F) dat[idx,"sampleNo"] <-1 ## yielding > dat var1 var2 sampleNo 1 1 40

I am doing some benchmarking of rsync. I am using the --bwlimit= option to throttle down rsync to predict its operation over slow communications links. I am using rsync 2.6.2 from the release site without any patches. I downloaded the release rather than pull from the CVS tree. I have 2 servers "wilber" (the remote archive) and "judy" (the local archive) connected with a gig

Forgive my novice question, but I am a new student of Linux working on presenting the ext3 journaling filesystem to my class. I seek any advice on how to visibly demonstrate (including a purposeful crash of a Linux box) the benefits of ext3 over ext2. I am not worthy to lick the bootstraps of this group, but I beg for any help! The problem I am having extends to even locating the .journal file