> > > > 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.
