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Hi! I have some data that looks like this up down percentaje uew_21 20 14 58.82 uew_20_5 27 40 40.29 uew_20 8 13 38.09 uew_19_5 17 42 28.81 So I have 4 experimental conditions and I am counting number of animals in the up and down compartment and the calculating the percentage, I want to know which one of the conditions is different from each other. If the data wouldn't be percentage

Hi Master... I am Rene Harb Hoecker and from Chile..... nice!!! I would like to ask you.......... so I am using pxe and when I configure this one with pxelinix.0 and this file read pxelinux.cfg and inside there is the config file default. it is work perfect....... default file say so : DAFAULT Gentoo1.4 LABEL Gentoo1.4 KERNEL linux APPEND nfsroot=3D192.168.10.10:/tftpboot/nodo1 IPAPPEND 1

The release notes state that gnumeric has been included in this distribution. Was it forgotten? -------------- next part -------------- A non-text attachment was scrubbed... Name: joe-harb.vcf Type: text/x-vcard Size: 298 bytes Desc: not available URL: <http://lists.centos.org/pipermail/centos/attachments/20050331/1a93e957/attachment-0005.vcf>

I am running Centos 4 on a Thinkpad r40 and it does not see any pcmcia cards. I know the socket is good because I had it working with Fedora Core 3. A funny thing though, once I updated my fedora kernel to a certain rev. (don't remember the version) the card socket no longer worked. Going back to an un-upgraded install of Fedora 3 worked. Has anyone seen this problem and worked this

Has anyone been successful with PCMCIA cards being seen by CentOS4? -------------- next part -------------- A non-text attachment was scrubbed... Name: joe-harb.vcf Type: text/x-vcard Size: 298 bytes Desc: not available URL: <http://lists.centos.org/pipermail/centos/attachments/20050425/7769c81f/attachment-0001.vcf>

I would really like some or any advice on how I can improve (or fix??) the following analysis. I hope I have provided a completely runnable code - it doesn't produce any errors for me. The resulting plot at the end shows a pretty poor correlation (just speaking visually here) to the test set. How can I improve the performance of the mapping and prediction? Here are some of the data

I have a data set with 10 variables, and about 8000 instances (or objects/rows/samples). In addition I have one more ('class') variable that I have about 10 instances for, but for which I wish to impute values for. I am a little confused how to go about doing this, mostly as I'm not well-versed in it. Do I train the SOM with a data object that contains just the first 10 variables

Hello, I have produced some segmented regressions with the segmented package by Viggo Mutteo. I have some example data and code below. I want to annotate the individual segments with the slope parameter (actually it would be nicer to annotate with 1000*slope and add some small amount of text as well). How can I do it? Reading the docs for segmented I can access all of the slope parameters via a

I am having difficulty understanding how I would constrain a data set by filtering out 'records' based on certain criteria. Using SQL I could query using 'select * from my.data where LithClass in ('sand', 'clay')' or some such. Using subset, there seem to be ghosts left behind (that is, all of the LithClass *.Labels* remain after subset) > dput(tcc)