Replies: 2 comments 2 replies
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Hello ZJ, I'm currently working on a secured server where I can only get a limited amount of RAM. However, in my latest application, I struggle to fit the model as the data frame is too large. I was wondering whether the package disk.frame would be useful in that setting... Kind regards, Clément |
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Thank you for your answer. I'll look into whether {felm} would allow me to
update sequentially my estimates.
…On Thu, Mar 25, 2021 at 1:05 PM evalparse ***@***.***> wrote:
Maybe I was supposed to write some other place, I apologize if this spot
is not appropriate...
It's fine. You could've started a new discussion too I think.
Does {felm} have progressive fit abilities? Or partial fit abilities? If
it has then disk.frame might be able to help.
Say if I have dataset a1 and a2 which together is my training data. Can I
train {felm} to fit on dataset a1 and get some coefficients, then add a2
to the model and update the coefficients? If {felm} can operate like that
then disk.frame can help.
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--
Clément Malgouyres
Économiste, Institut des politiques publiques (IPP) www.ipp.eu,
Chercheur affilié à Paris School of Economics (PSE)
Site web: https://sites.google.com/site/clementmalgouyres
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