[R] Converting data frame to array?

[John Fox]

Dear Thomas,

I doubt whether there's anything useful that you can do with 300 predictors
and only 10 observations. A naïve application of variable selection will
likely allow you to account perfectly for the variation in the response
variable just by capitalizing on chance.

John 

> -----Original Message-----
> From: TAPO (Thomas Agersten Poulsen) [mailto:tapo at novozymes.com] 
> Sent: Monday, May 31, 2004 2:26 PM
> To: John Fox
> Cc: r-help at stat.math.ethz.ch
> Subject: RE: [R] Converting data frame to array?
> 
> Dear John,
> 
> 	Thank you for your helpful answer. I was obviously 
> being stupid, as I have, as you point out, more predictors 
> than observations.
> 
> 	What I was hoping to get was some sort of an 
> "explaining linear combination" of my predictors: which 
> predictors are important for the results I see (if any) and 
> which are irrelevant. 
> 
> 	Any hints on how to achieve that?
> 	
> Cheers
> Thomas
> 
> -----Original Message-----
> From: John Fox [mailto:jfox at mcmaster.ca]
> Sent: 29. maj 2004 01:24
> To: TAPO (Thomas Agersten Poulsen)
> Cc: r-help at stat.math.ethz.ch
> Subject: RE: [R] Converting data frame to array?
> 
> 
> Dear Thomas,
> 
> In fact, the more common way to fit a linear regression in R is to use
> variables in a data frame (or list) along with a model formula
> specifying the model. All of this is explained in the 
> Introduction to R
> manual that is distributed with R: see, in particular, Sec. 
> 6.3 on data
> frames, Sec. 7 on reading data from files, and Sec. 11 on statistical
> models.
> 
> Given two data frames, say d1 and d2, the first containing, e.g.,
> observations on variables x1 and x2 and the second on y, one could do
> lm(y ~ x1 + x2, data=c(x1, x2)) or lm(y ~ x1 + x2, data=data.frame(x1,
> x2)). 
> 
> That said, it's not altogether clear to me what it is that 
> you're trying
> to do. Are there 10 observations on 300 variables in the first data
> frame, constituting the predictors, and 10 observations on 1 
> variable in
> the second data frame, constituting the response? If so, you have many
> more predictors than observations, and it's not reasonable to 
> perform a
> regression. Of course, I may not have this straight.
> 
> I hope this helps,
>  John
> 
> > -----Original Message-----
> > From: r-help-bounces at stat.math.ethz.ch
> > [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of TAPO 
> > (Thomas Agersten Poulsen)
> > Sent: Friday, May 28, 2004 2:11 PM
> > To: r-help at stat.math.ethz.ch
> > Subject: [R] Converting data frame to array?
> > 
> > Dear List,
> > 
> > 	Please bear with a poor newbee, who might be doing
> > everything backwards (I was brought up in pure math).
> > 
> > 	I want to make a simple multi-linear regression on a
> > set of data. I did some expreiments, and if X is a 4 by 2 
> > array and Y is a 4 by
> > 1 array, I can do a linear regression by lm(y~x). 
> > 
> > 	Now I have a tab-delimited text file with 10 rows of
> > 300 measurements and an other file with 10 rows of one value 
> > each. When I read in those files using read.delim(), I get 
> > data frames, and apparently I can no longer do the 
> > multi-linear regression.
> > 
> > 	Is there a way to convert the data frames into arrays,
> > or am I going the wrong way about this?
> > 
> > Sincerely
> > Thomas Poulsen
> > 
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