Here's a simplified example p<-1:80+rnorm(80) dim(p)<-c(2,2,2,10)
We could say that the 4-d array p consists of 2*2*2 = 8 vectors of length 10. So what I'm asking for is a fast way to perform a linear fit to all those vectors. I'm sorry if I'm causing you to have a headache with all those dimensions :) Kostas > Well, could you provide a little bit more information regarding what > you are trying to do (e.g., reproducible example). > > Best, > Dimitris > > ---- > Dimitris Rizopoulos > Biostatistical Centre > School of Public Health > Catholic University of Leuven > > Address: Kapucijnenvoer 35, Leuven, Belgium > Tel: +32/(0)16/336899 > Fax: +32/(0)16/337015 > Web: http://med.kuleuven.be/biostat/ > http://www.student.kuleuven.be/~m0390867/dimitris.htm > > > ----- Original Message ----- > From: "Costas Douvis" <[EMAIL PROTECTED]> > To: <r-help@r-project.org>; "Mark Leeds" <[EMAIL PROTECTED]>; > "Dimitris Rizopoulos" <[EMAIL PROTECTED]> > Cc: "Chuck Cleland" <[EMAIL PROTECTED]> > Sent: Wednesday, April 09, 2008 3:44 PM > Subject: Re: [R] apply lm() for all the columns of a matrix > > >> Thank you all very much for replying. Of course you are absolutely >> right >> but unfortunately I really deal with the case of a 4-d matrix so >> what you >> said does not apply. I should have specified but being a new R user >> I >> hadn't realized the difference between a matrix and an array. >> >> So please tell me if you know a fast way (not using a loop) to >> perform a >> linear fit on all the vectors of the 4-th dimension of a 4-d array. >> >> Thanks again >> Kostas >> >>> If you have the same design matrix then you can specify a matrix of >>> responses in lm(), e.g., >>> >>> Y <- matrix(rnorm(100*10), 100, 10) >>> x <- rnorm(100) >>> >>> fit <- lm(Y ~ x) >>> fit >>> summary(fit) >>> >>> >>> I hope it helps. >>> >>> Best, >>> Dimitris >>> >>> ---- >>> Dimitris Rizopoulos >>> Biostatistical Centre >>> School of Public Health >>> Catholic University of Leuven >>> >>> Address: Kapucijnenvoer 35, Leuven, Belgium >>> Tel: +32/(0)16/336899 >>> Fax: +32/(0)16/337015 >>> Web: http://med.kuleuven.be/biostat/ >>> http://www.student.kuleuven.be/~m0390867/dimitris.htm >>> >>> >>> ----- Original Message ----- >>> From: "Costas Douvis" <[EMAIL PROTECTED]> >>> To: <r-help@r-project.org> >>> Sent: Wednesday, April 09, 2008 12:55 PM >>> Subject: [R] apply lm() for all the columns of a matrix >>> >>> >>>> Hi all, >>>> >>>> My question is not really urgent. I can write a loop and solve the >>>> problem. But I know that I'll be in a similar situation many more >>>> times so >>>> it would be useful to find out the answer >>>> >>>> Is there a fast way to perform linear fit to all the columns of a >>>> matrix? >>>> (or in the one dimension of a multi-dimensional array.) I'm >>>> talking >>>> about >>>> many single linear fits, not about a multiple fit. I thought that >>>> a >>>> combination of apply and lm would do it but I can't make it work >>>> >>>> Thank you >>>> Kostas >>>> >>>> >>>> -- >>>> Kostas Douvis >>>> PhD Student >>>> University of Athens - Department of Geography and Climatology >>>> Academy of Athens - Research Centre for Atmospheric Physics and >>>> Climatology >>>> email: [EMAIL PROTECTED] >>>> tel: +30-210-8832048 >>>> >>>> ______________________________________________ >>>> R-help@r-project.org mailing list >>>> https://stat.ethz.ch/mailman/listinfo/r-help >>>> PLEASE do read the posting guide >>>> http://www.R-project.org/posting-guide.html >>>> and provide commented, minimal, self-contained, reproducible code. >>>> >>> >>> >>> Disclaimer: http://www.kuleuven.be/cwis/email_disclaimer.htm >>> >>> >> >> > > > Disclaimer: http://www.kuleuven.be/cwis/email_disclaimer.htm > > -- Kostas Douvis PhD Student University of Athens - Department of Geography and Climatology Academy of Athens - Research Centre for Atmospheric Physics and Climatology email: [EMAIL PROTECTED] tel: +30-210-8832048 ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
