Dear Professors Koenker and Varadhan, Thank you for your detailed and engaging replies. The (very) muddy waters clear slowly, but only if I keep moving my hands!
Kind regards, Mark Difford. Mark Difford Ph.D. candidate, Botany Department, Nelson Mandela Metropolitan University, Port Elizabeth, SA. ----- Original Message ---- From: roger koenker <[EMAIL PROTECTED]> To: Mark Difford <[EMAIL PROTECTED]> Cc: R-help list <[email protected]> Sent: Wednesday, 20 December, 2006 3:57:02 PM 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. Send instant messages to your online friends http://uk.messenger.yahoo.com ______________________________________________ [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.
