[R] non parametric regression

Hi All, I am relatively new to R. I am having a problem with a regression I am trying to run. Here is what I enter > npregbw(dat=mydata,formula=T~factor(OriginStateID)+factor(DestinationstateID)+factor(HomeDummy)+factor(BorderDummy)+lnDistance > +lnOriginStateremoteness + lnDestinationStateremot

Re: [R] Non-parametric regression

Just to be correct : gam is mentioned on the page Tal linked to, but is a semi-parametric approach using maximum likelihood. It stays valid though. Another thing : you detect non-normality. But can you use a Poisson distribution for example? The framework of generalized linear models and generaliz

Re: [R] Non-parametric regression

On Jul 9, 2010, at 4:01 AM, Ralf B wrote: I have two data sets, each a vector of 1000 numbers, each vector representing a distribution (i.e. 1000 numbers each of which representing a frequency at one point on a scale between 1 and 1000). For similfication, here an short version with only 5 poin

Re: [R] Non-parametric regression

>From reviewing the first google page result for "Non-parametric regression R", I hope this link will prove useful: http://socserv.mcmaster.ca/jfox/Courses/Oxford-2005/R-nonparametric-regression.html Contact Details:--- Contact

[R] Non-parametric regression

I have two data sets, each a vector of 1000 numbers, each vector representing a distribution (i.e. 1000 numbers each of which representing a frequency at one point on a scale between 1 and 1000). For similfication, here an short version with only 5 points. a <- c(8,10,8,12,4) b <- c(7,11,8,10,5)

[R] non-parametric regression with a convexity constraint

I would like to know if there's a package in R that enables to get a non-parametric regression (OLS, not quantile) that would have a positive (or negative) convexity constraint, as well as monotonicity. Right now, I have only found two packages (fdrtool and cir) that enable to impose only monoto