R help - Oct 2005 - run many linear regressions against the same independent variables in batch

R function 
lm(response ~ term)
allows me to run a linear regression on a single response vector. For 
example, I have recent one year historical prices for a stock and S&P 
index. I can run regression of the stock prices (as response vector) 
against the S&P index prices (as term vector).

Now assume I have 1000 stocks to run the above regressions (against the 
same S&P index prices). The only way I know is that I write a loop. Within 
each loop I do the regression for one stock price.

Is there a batch method to run the 1000 regressions in one shot? Note that 
this functionality is available in SAS (the SAS procedure "reg").

Actually, some times we run such regressions for about 300K securities. 
Performing regressions in loop takes a long time. On the contrary, running 
on SAS is much faster.

Thank you in advance.

Heng Sun
212-855-5754

Director
Quantitative Risk
Depository Trust and Clearing Corporation

	[[alternative HTML version deleted]]

This runs a regression of each column (except the first)
of matrix state.x77 against the first:

lm(state.x77[,-1] ~ state.x77[,1])

On 10/14/05, Heng Sun <HSun at dtcc.com> wrote:
> R function
> lm(response ~ term)
> allows me to run a linear regression on a single response vector. For
> example, I have recent one year historical prices for a stock and S&P
> index. I can run regression of the stock prices (as response vector)
> against the S&P index prices (as term vector).
>
> Now assume I have 1000 stocks to run the above regressions (against the
> same S&P index prices). The only way I know is that I write a loop.
Within
> each loop I do the regression for one stock price.
>
> Is there a batch method to run the 1000 regressions in one shot? Note that
> this functionality is available in SAS (the SAS procedure "reg").
>
> Actually, some times we run such regressions for about 300K securities.
> Performing regressions in loop takes a long time. On the contrary, running
> on SAS is much faster.
>
> Thank you in advance.
>
> Heng Sun
> 212-855-5754
>
> Director
> Quantitative Risk
> Depository Trust and Clearing Corporation
>
>        [[alternative HTML version deleted]]
>
> ______________________________________________
> R-help at stat.math.ethz.ch mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide!
http://www.R-project.org/posting-guide.html
>

I have always used lsfit() for this, but have been told that lm() is
preferred, and I note the help for lm() states

 If 'response' is a matrix a linear model is fitted separately by
     least-squares to each column of the matrix.

Reid Huntsinger




-----Original Message-----
From: r-help-bounces at stat.math.ethz.ch
[mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Heng Sun
Sent: Friday, October 14, 2005 11:56 AM
To: r-help at stat.math.ethz.ch
Subject: [R] run many linear regressions against the same independent
variables in batch


R function 
lm(response ~ term)
allows me to run a linear regression on a single response vector. For 
example, I have recent one year historical prices for a stock and S&P 
index. I can run regression of the stock prices (as response vector) 
against the S&P index prices (as term vector).

Now assume I have 1000 stocks to run the above regressions (against the 
same S&P index prices). The only way I know is that I write a loop. Within 
each loop I do the regression for one stock price.

Is there a batch method to run the 1000 regressions in one shot? Note that 
this functionality is available in SAS (the SAS procedure "reg").

Actually, some times we run such regressions for about 300K securities. 
Performing regressions in loop takes a long time. On the contrary, running 
on SAS is much faster.

Thank you in advance.

Heng Sun
212-855-5754

Director
Quantitative Risk
Depository Trust and Clearing Corporation

	[[alternative HTML version deleted]]

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