It's not your questions, Cobbler, but could you PLEASE just do what we asked
for?
Copy-paste the following in R and copy-paste ALL output you get in your next
mail.

test.vowel <- vowel_features[,1:10]
test.mask <- mask_features[,1:10]
dput(test.vowel)
dput(test.mask)

I don't know whether your vowel_features is a list or a data-frame (which is
technically also a list). But I know for sure that vowel_features[15] is NOT
giving you a column. Probably it has to be vowel_features[,15]. So start
with that one, and I'll take a look at the rest to get your lda running.

Cheers
Joris

On Sat, May 29, 2010 at 6:53 PM, cobbler_squad <la.foma@gmail.com> wrote:

>
> Thanks for being patient with me.
>
> I guess my problem is with understand how grouping in this particular case
> is used:
>
> one of the sample codes I found online
> (http://www.statmethods.net/advstats/discriminant.html)
> library(MASS)
> fit <- lda(G ~ x1 + x2 + x3, data=mydata, na.action="na.omit", CV=TRUE)
>
> the "mydata" file in my case is the 3dmaskdump file with 52 columns and 671
> rows (all values range between 0 and 1 after they're scaled)
>
> the other file, what I assumed was the "grouping file" (or the
> "vowel_feature") is the file that defines features for the vowels (i.e.
> column 1 of the file is vowel name (a, i, u) and every other column in a
> distinct combination of 0's and 1's defining the vowel (so this file has 26
> columns and 254 rows). Therefore, every column that follows represents a
> particular "feature" of that vowel.. (hope this makes sense!!)
>
> So, the reason I wanted to return G <- vowel_feature[15] in my previous
> post
> is because I need to extract a column that represents "backness" of the
> vowel  (while other columns represent "roundedness", "nasalization"
> features, etc). So what (in my mind) G <- vowel_feature[15] would return is
> 1 column which is 254 rows long with 0's and 1's in it.
> i.e.
>
> 1       0
> 2       1
> 3       1
> 4       0
> ...
> ..
> .
> 254    1
>
> I am a novice with R (so I know my questions are pretty dumb!), but I
> really
> hope I clarified my confusion a bit better.  I very much appreciate your
> help.
>
> Looking forward to your replies.
>
> Thank you again,
> Cobbler
>
>
> --
> View this message in context:
> http://r.789695.n4.nabble.com/Linear-Discriminant-Analysis-in-R-tp2231922p2235777.html
> Sent from the R help mailing list archive at Nabble.com.
>
> ______________________________________________
> R-help@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>



-- 
Joris Meys
Statistical Consultant

Ghent University
Faculty of Bioscience Engineering
Department of Applied mathematics, biometrics and process control

Coupure Links 653
B-9000 Gent

tel : +32 9 264 59 87
Joris.Meys@Ugent.be
-------------------------------
Disclaimer : http://helpdesk.ugent.be/e-maildisclaimer.php

	[[alternative HTML version deleted]]

