Re: [R] local regression using loess
cindy Guo wrote: Hi, All, I have a dataset with binary response ( 0 and 1) and some numerical covariates. I know I can use logistic regression to fit the data. But I want to consider more locally. So I am wondering how can I fit the data with 'loess' function in R? And what will be the response: 0/1 or the probability in either group like in logistic regression? Thank you, Cindy [[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. Why don't you fit a GAM with a logistic link function and binomial distirbution? Alain - Dr. Alain F. Zuur First author of: 1. Analysing Ecological Data (2007). Zuur, AF, Ieno, EN and Smith, GM. Springer. 680 p. 2. Mixed effects models and extensions in ecology with R. (2009). Zuur, AF, Ieno, EN, Walker, N, Saveliev, AA, and Smith, GM. Springer. 3. A Beginner's Guide to R (2009). Zuur, AF, Ieno, EN, Meesters, EHWG. Springer Statistical consultancy, courses, data analysis and software Highland Statistics Ltd. 6 Laverock road UK - AB41 6FN Newburgh Email: highs...@highstat.com URL: www.highstat.com -- View this message in context: http://www.nabble.com/local-regression-using-loess-tp24689834p24696908.html Sent from the R help mailing list archive at Nabble.com. __ 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] local regression using loess
Actually, loess is much more than an interpolant. I wouldn't even call it that. It is a local regression technique that comes with all the equipment you get in classical regression. But it is meant for normal-like errors, which is not what you have. -- This is misleading. The local smoother part makes a big difference. For example df (and standard tests, consequently)are not defined as in conventional multiple regression (though the enp argument gives you something like df). Also, it was specifically designed for _non_-normal errors -- specifically, long-tailed distributions -- via use of the symmetric family argument which fits via a re-descending M-estimator not Gaussian likelihood = least squares. But you are certainly free to characterize it as you think appropriate if you do not think interpolant is reasonable... -- Bert I would recommend that you take a look at the locfit package. It fits local likelihood models. I've never tried it with binary data, but if y is your 0/1 response and x is a covariate, you might try something like: locfit(y ~ x, ..., family=binomial) If you have a good library at your disposal, try picking up Loader's book Local Regression and Likelihood. __ 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.
Re: [R] local regression using loess
Are X1 and X2 both numeric? You might want to get them on equivalent scales, and also play around with the smoothing parameter. Try something like: fit - locfit(Y ~ lp(X1, X2, nn=___, scale=TRUE), family=binomial) and see what happens for different values of nn (try values between 0 and 1 and then some larger than one). I can't be much more help without data. On Jul 27, 2009, at 9:41 PM, cindy Guo wrote: Hi, Ryan, Thank you for the information. I tried it. But there are some error messages. When I use fit - locfit(Y~X1*X2,family='binomial'), the error message is error lfproc(x, y, weights = weights, cens = cens, base = base, geth = geth, : compparcomp: parameters out of bounds And when I use fit - locfit(Y~X1*X2), the error message is error lfproc(x, y, weights = weights, cens = cens, base = base, geth = geth, : newsplit: out of vertex space This happens sometimes, not every time for different data. Do you know what's the reason? Thank you, Cindy On Mon, Jul 27, 2009 at 5:25 PM, Ryan rha...@purdue.edu wrote: Hi, All, I have a dataset with binary response ( 0 and 1) and some numerical covariates. I know I can use logistic regression to fit the data. But I want to consider more locally. So I am wondering how can I fit the data with 'loess' function in R? And what will be the response: 0/1 or the probability in either group like in logistic regression? -- Neither. Loess is an algorithm that smoothly interpolates the data. It makes no claim of modeling the probability for a binary response variable. -- Bert Gunter Genentech Nonclinical Statistics Thank you, Cindy [[alternative HTML version deleted]] Actually, loess is much more than an interpolant. I wouldn't even call it that. It is a local regression technique that comes with all the equipment you get in classical regression. But it is meant for normal-like errors, which is not what you have. I would recommend that you take a look at the locfit package. It fits local likelihood models. I've never tried it with binary data, but if y is your 0/1 response and x is a covariate, you might try something like: locfit(y ~ x, ..., family=binomial) If you have a good library at your disposal, try picking up Loader's book Local Regression and Likelihood. __ 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. [[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] local regression using loess
Bert Gunter gunter.berton at gene.com writes: Actually, loess is much more than an interpolant. I wouldn't even call it that. It is a local regression technique that comes with all the equipment you get in classical regression. But it is meant for normal-like errors, which is not what you have. Bert - when I hear interpolate, I think of connecting the data points, like using something like divided differences or hermite interpolation, so I thought that's what you meant. Sorry for the misunderstanding. True that loess was designed to be robust, but when I said it is meant for normal-like errors, I was referring to loess with statistical procedures analagous to the classical regression setting, such as confidence intervals, anova, etc. (see Locally Weighted Regression: An Approach to Regression Analysis by Local Fitting, 1988). __ 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] local regression using loess
Bert, Ryan, Alain, You suggestions are very helpful. Thank you. I learned a lot from the discussion. Cindy On Tue, Jul 28, 2009 at 8:53 AM, Ryan rha...@purdue.edu wrote: Bert Gunter gunter.berton at gene.com writes: Actually, loess is much more than an interpolant. I wouldn't even call it that. It is a local regression technique that comes with all the equipment you get in classical regression. But it is meant for normal-like errors, which is not what you have. Bert - when I hear interpolate, I think of connecting the data points, like using something like divided differences or hermite interpolation, so I thought that's what you meant. Sorry for the misunderstanding. True that loess was designed to be robust, but when I said it is meant for normal-like errors, I was referring to loess with statistical procedures analagous to the classical regression setting, such as confidence intervals, anova, etc. (see Locally Weighted Regression: An Approach to Regression Analysis by Local Fitting, 1988). __ 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.htmlhttp://www.r-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. [[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] local regression using loess
-Original Message- From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On Behalf Of cindy Guo Sent: Monday, July 27, 2009 4:06 PM To: r-help@r-project.org Subject: [R] local regression using loess Hi, All, I have a dataset with binary response ( 0 and 1) and some numerical covariates. I know I can use logistic regression to fit the data. But I want to consider more locally. So I am wondering how can I fit the data with 'loess' function in R? And what will be the response: 0/1 or the probability in either group like in logistic regression? -- Neither. Loess is an algorithm that smoothly interpolates the data. It makes no claim of modeling the probability for a binary response variable. -- Bert Gunter Genentech Nonclinical Statistics Thank you, Cindy [[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. __ 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] local regression using loess
Hi, Bert, Thanks for the response. But then in this case, can I use loess to fit the data? If yes, then how to interpret the results? Cindy On Mon, Jul 27, 2009 at 4:32 PM, Bert Gunter gunter.ber...@gene.com wrote: -Original Message- From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On Behalf Of cindy Guo Sent: Monday, July 27, 2009 4:06 PM To: r-help@r-project.org Subject: [R] local regression using loess Hi, All, I have a dataset with binary response ( 0 and 1) and some numerical covariates. I know I can use logistic regression to fit the data. But I want to consider more locally. So I am wondering how can I fit the data with 'loess' function in R? And what will be the response: 0/1 or the probability in either group like in logistic regression? -- Neither. Loess is an algorithm that smoothly interpolates the data. It makes no claim of modeling the probability for a binary response variable. -- Bert Gunter Genentech Nonclinical Statistics Thank you, Cindy [[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.htmlhttp://www.r-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. [[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] local regression using loess
Hi, All, I have a dataset with binary response ( 0 and 1) and some numerical covariates. I know I can use logistic regression to fit the data. But I want to consider more locally. So I am wondering how can I fit the data with 'loess' function in R? And what will be the response: 0/1 or the probability in either group like in logistic regression? -- Neither. Loess is an algorithm that smoothly interpolates the data. It makes no claim of modeling the probability for a binary response variable. -- Bert Gunter Genentech Nonclinical Statistics Thank you, Cindy [[alternative HTML version deleted]] Actually, loess is much more than an interpolant. I wouldn't even call it that. It is a local regression technique that comes with all the equipment you get in classical regression. But it is meant for normal-like errors, which is not what you have. I would recommend that you take a look at the locfit package. It fits local likelihood models. I've never tried it with binary data, but if y is your 0/1 response and x is a covariate, you might try something like: locfit(y ~ x, ..., family=binomial) If you have a good library at your disposal, try picking up Loader's book Local Regression and Likelihood. __ 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] local regression using loess
Hi, Ryan, Thank you for the information. I tried it. But there are some error messages. When I use fit - locfit(Y~X1*X2,family='binomial'), the error message is error lfproc(x, y, weights = weights, cens = cens, base = base, geth = geth, : compparcomp: parameters out of bounds And when I use fit - locfit(Y~X1*X2), the error message is error lfproc(x, y, weights = weights, cens = cens, base = base, geth = geth, : newsplit: out of vertex space This happens sometimes, not every time for different data. Do you know what's the reason? Thank you, Cindy On Mon, Jul 27, 2009 at 5:25 PM, Ryan rha...@purdue.edu wrote: Hi, All, I have a dataset with binary response ( 0 and 1) and some numerical covariates. I know I can use logistic regression to fit the data. But I want to consider more locally. So I am wondering how can I fit the data with 'loess' function in R? And what will be the response: 0/1 or the probability in either group like in logistic regression? -- Neither. Loess is an algorithm that smoothly interpolates the data. It makes no claim of modeling the probability for a binary response variable. -- Bert Gunter Genentech Nonclinical Statistics Thank you, Cindy [[alternative HTML version deleted]] Actually, loess is much more than an interpolant. I wouldn't even call it that. It is a local regression technique that comes with all the equipment you get in classical regression. But it is meant for normal-like errors, which is not what you have. I would recommend that you take a look at the locfit package. It fits local likelihood models. I've never tried it with binary data, but if y is your 0/1 response and x is a covariate, you might try something like: locfit(y ~ x, ..., family=binomial) If you have a good library at your disposal, try picking up Loader's book Local Regression and Likelihood. __ 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.htmlhttp://www.r-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. [[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.
