[R] Regression by factor using "sapply"

[Paul Hiemstra]

 I would take a look at the ddply function from the plyr package.
Without a reproducible example (most importantly an example dataset) I
cannot give you some example code.

cheers,
Paul

On 08/24/2011 05:51 PM, elh wrote:
> Apologies for the elementary nature of the question (yes, I'm another
> newbie)...
>
> I'd like to perform a multiple regression on a single data set containing a
> representation of energy consumption and temperatures containing account
> number, usage (KWh), heating degree days (HDD) and cooling degree (CDD)
> days.  I want to get the coefficients back from the following equation:  
>     lm(AvgKWh ~ AvgHDD + AvgCDD, data=usage)
>
> Given that the data set contains the usage of different accounts (e.g. some
> large energy users and some small energy users) I do not want to perform the
> equation just one time.  Instead, I want to re-calculate the coefficients
> (and associated measures of goodness of fit) for each account using the same
> equation and return the corresponding coefficients by the account number
> identifier.   
>
> I thought I had figured out how to do this using  "by" and "sapply" formula
> but I keep getting an error message of: "$ operator is invalid for atomic
> vectors"
>
> Here is what I've bee trying to use
> # data is stored in a table called "usage"; other than the "ActNo" field,
> all the fields are numeric
> byDD <- function(data) {lm(AvgKWh~ AvgHDD + AvgCDD, data=data)}
> byActNo <- by(usage, usage$ActNo, FUN=byDD)
> sapply(byActNo, summary(byActno)$coef)
>
> Thanks in advance!  I'm sure a similar question has been covered somewhere
> but everytime I follow the message stream I hit a deadend.
>
> --
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> Sent from the R help mailing list archive at Nabble.com.
>
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-- 
Paul Hiemstra, Ph.D.
Global Climate Division
Royal Netherlands Meteorological Institute (KNMI)
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