Message-ID: <f97ef02f457c.49b92b96@johnshopkins.edu>
Date: 2009-03-12T19:34:46Z
From: Ravi Varadhan
Subject: stats lm() function
In-Reply-To: <22482054.post@talk.nabble.com>
Look at:
?update
For example:
lm.obj <- lm (y ~ x1 + ... + x300)
lm.obj1 <- update(lm.obj, . ~ . - x1)
lm.obj2 <- update(lm.obj1, . ~ . - x2)
Ravi.
____________________________________________________________________
Ravi Varadhan, Ph.D.
Assistant Professor,
Division of Geriatric Medicine and Gerontology
School of Medicine
Johns Hopkins University
Ph. (410) 502-2619
email: rvaradhan at jhmi.edu
----- Original Message -----
From: ph84 <masterodspam at gmx.de>
Date: Thursday, March 12, 2009 3:28 pm
Subject: [R] stats lm() function
To: r-help at r-project.org
> Hi,
>
> Im using the lm() function where the formula is quite big (300 arguments)
> and the data is a frame of 3000 values.
>
> This is running in a loop where in each step the formula is reduced
> by one
> argument, and the lm command is called again (to check which
> arguments are
> useful) .
>
> This takes 1-2 minutes.
> Is there a way to speed this up?
> i checked the code of the lm function and its seems that its
> preparing the
> data and then calls lm.Fit(). i thought about just doing this praparing
> stuff first and only call lm.fit() 300 times.
>
>
> --
> View this message in context:
> Sent from the R help mailing list archive at Nabble.com.
>
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>
> PLEASE do read the posting guide
> and provide commented, minimal, self-contained, reproducible code.