On Dec 20, 2006, at 8:43 AM, Ravi Varadhan wrote:
> Dear Roger, > > Is it possible to combine the two ideas that you mentioned: (1) > algorithmic > approaches of Breiman, Friedman, and others that achieve > flexibility in the > predictor space, and (2) robust and flexible regression like QR > that achieve > flexibility in the response space, so as to achieve complete > flexibility? > If it is possible, are you or anyone else in the R community > working on > this? > > There are some tentative steps in this direction. One is the rqss() fitting in my quantreg package which does QR fitting with additive models using total variation as a roughness penalty for nonlinear terms. Another, along more tree structured lines, is Nicolai Meinshausen's quantregforest package. > > -----Original Message----- > From: [EMAIL PROTECTED] > [mailto:[EMAIL PROTECTED] On Behalf Of roger koenker > Sent: Wednesday, December 20, 2006 8:57 AM > To: Mark Difford > Cc: R-help list > Subject: Re: [R] RuleFit & quantreg: partial dependence plots; > showing an > effect > > They are entirely different: Rulefit is a fiendishly clever > combination of decision tree formulation > of models and L1-regularization intended to select parsimonious fits > to very complicated > responses yielding e.g. piecewise constant functions. Rulefit > estimates the conditional > mean of the response over the covariate space, but permits a very > flexible, but linear in > parameters specifications of the covariate effects on the conditional > mean. The quantile > regression plotting you refer to adopts a fixed, linear specification > for conditional quantile > functions and given that specification depicts how the covariates > influence the various > conditional quantiles of the response. Thus, roughly speaking, > Rulefit is focused on > flexibility in the x-space, maintaining the classical conditional > mean objective; while > QR is trying to be more flexible in the y-direction, and maintaining > a fixed, linear > in parameters specification for the covariate effects at each > quantile. > > > url: www.econ.uiuc.edu/~roger Roger Koenker > email [EMAIL PROTECTED] Department of Economics > vox: 217-333-4558 University of Illinois > fax: 217-244-6678 Champaign, IL 61820 > > > On Dec 20, 2006, at 4:17 AM, Mark Difford wrote: > >> Dear List, >> >> I would greatly appreciate help on the following matter: >> >> The RuleFit program of Professor Friedman uses partial dependence >> plots >> to explore the effect of an explanatory variable on the response >> variable, after accounting for the average effects of the other >> variables. The plot method [plot(summary(rq(y ~ x1 + x2, >> t=seq(.1,.9,.05))))] of Professor Koenker's quantreg program >> appears to >> do the same thing. >> >> >> Question: >> Is there a difference between these two types of plot in the manner >> in which they depict the relationship between explanatory variables >> and the response variable ? >> >> Thank you inav for your help. >> >> Regards, >> Mark Difford. >> >> ------------------------------------------------------------- >> Mark Difford >> Ph.D. candidate, Botany Department, >> Nelson Mandela Metropolitan University, >> Port Elizabeth, SA. >> >> ______________________________________________ >> [email protected] 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. > > ______________________________________________ > [email protected] 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. > > ______________________________________________ > [email protected] 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. ______________________________________________ [email protected] 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.
