[R] Datasets in R
I´m trying to find datasets that will give me residuals, after applying the lm function, with no normality, non linearity, and heteroscedacity so I can try to exemplify those cases in the linear regression model. Can you give any advice on what datasets would be appropiate? I can´t use the ones in the alr3 package because those have already been seen in class. Thank you very much :-) natorro -- This message has been scanned for viruses and dangerous content by MailScanner, and is believed to be clean. __ 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.
Re: [R] Datasets in R
Carlos López wrote: I´m trying to find datasets that will give me residuals, after applying the lm function, with no normality, non linearity, and heteroscedacity so I can try to exemplify those cases in the linear regression model. Can you give any advice on what datasets would be appropiate? I can´t use the ones in the alr3 package because those have already been seen in class. Thank you very much :-) natorro if you know what you are looking for (or not looking for), wouldn't it be the easiest and fastest thing to do to simulate such a dataset yourself? Best, Roland __ 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.
Re: [R] Datasets in R
Carlos, There are many sources of real datasets (in R itself, on the web), you just need to look a little. For teaching purposes, I think it is always better to use real datasets than to use simulated ones. One thing bothers me, though. You imply that in all the examples you have the data are well fit with linear models, the residuals are normal and there is no sign of heteroscedacity. That sounds a very unusual set of examples! Best Antony > From: Roland Rau <[EMAIL PROTECTED]> > Date: 30 May 2008 12:23:17 AM GMT+02:00 > To: Carlos López <[EMAIL PROTECTED]> > Cc: r-help@r-project.org > Subject: Re: [R] Datasets in R > > > Carlos López wrote: >> I´m trying to find datasets that will give me residuals, after >> applying the lm function, with no normality, non linearity, and >> heteroscedacity so I can try to exemplify >> those cases in the linear regression model. Can you give any advice >> on what datasets would be appropiate? I can´t use the ones in the >> alr3 package because those have >> already been seen in class. >> Thank you very much :-) >> natorro > if you know what you are looking for (or not looking for), wouldn't > it be the easiest and fastest thing to do to simulate such a dataset > yourself? > > Best, > Roland [[alternative HTML version deleted]] __ 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.
Re: [R] Datasets in R
Hi Carlos, Carlos López wrote: I´m trying to find datasets that will give me residuals, after applying the lm function, with no normality, non linearity, and heteroscedacity so I can try to exemplify those cases in the linear regression model. Can you give any advice on what datasets would be appropiate? I can´t use the ones in the alr3 package because those have already been seen in class. Thank you very much :-) natorro if you don't want to simulate your own data, you might have a look at the NIST Reference Datasets http://www.itl.nist.gov/div898/strd/ I hope this help? Roland __ 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.
Re: [R] Datasets in R
Dear Roland and Carlos, There are some examples in my R and S-PLUS Companion to Applied Regression; the data sets are in the car package. I hope this helps, John -- John Fox, Professor Department of Sociology McMaster University Hamilton, Ontario, Canada web: socserv.mcmaster.ca/jfox > -Original Message- > From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On > Behalf Of Roland Rau > Sent: May-30-08 10:35 AM > To: Carlos López > Cc: r-help@r-project.org > Subject: Re: [R] Datasets in R > > Hi Carlos, > > Carlos López wrote: > > I´m trying to find datasets that will give me residuals, after applying > > the lm function, with no normality, non linearity, and heteroscedacity > > so I can try to exemplify > > those cases in the linear regression model. Can you give any advice on > > what datasets would be appropiate? I can´t use the ones in the alr3 > > package because those have > > already been seen in class. > > > > Thank you very much :-) > > natorro > > > > if you don't want to simulate your own data, you might have a look at > the NIST Reference Datasets > http://www.itl.nist.gov/div898/strd/ > > I hope this help? > Roland > > __ > 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. __ 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.
