[R] Robust estimation of a geometric random variable

Hi, I have a bunch of data which is assumed to be instances of a geometric random variable with outliers. How can I do a robust estimation of the parameter p so that the effect of outliers is minimized? As a part of the estimation process, I also need to know which are the outliers in the

[R] robust estimation

Hi, I have been looking through all packages but I cannot find a routine for LAD-regression (L1-norm-regression). Is there none? Willi __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide

Re: [R] robust estimation

Willi, try this: install.packages(sos) library(sos) findFn(L1 norm regression) I find 34 hits but you'd have to look them over to see if any of them are the sort of thing you want. HTH, Bryan Prof. Bryan Hanson Dept of Chemistry Biochemistry DePauw University 602 S.

Re: [R] robust estimation

On Mar 11, 2011, at 7:31 AM, Wilhelm Caspary wrote: Hi, I have been looking through all packages but I cannot find a routine for LAD-regression (L1-norm-regression). Is there none? (In addition to the pkg::sos search results the help archives can also be reviewed.)

Re: [R] robust estimation

Is the L1 norm not equivalent to quantile regression for the 0.5th quantile? If so, quantreg would do it using rq with the defult value for tau. S Ellison Wilhelm Caspary wilhelm.casp...@unibw.de 11/03/2011 12:31 Hi, I have been looking through all packages but I cannot find a routine for

Re: [R] Robust estimation of variance components for a nested design

, modeling the random effects with t distributions. No software were publicly available, as far as I know. Andy From: S Ellison Sent: Thursday, March 11, 2010 9:56 AM To: r-help at r-project.org Subject: [R] Robust estimation of variance components for a nested design One of my colleagues has

Re: [R] Robust estimation of variance components for a nested design

If you mean using random effects which have a fat-tailed distribution this has been available in AD Model Builder's random effects package for some time now. The general idea is to start with a random effect assumed to be standard normal and then to transform it by the cumulative dist function

[R] Robust estimation of variance components for a nested design

of variance. Nothing in my collection of R robust estimation packages (robust, robustbase and MASS being the obvious three) or on the Robust task view seems to cover this, though it's entirely possible I've missed something. Any pointers (to R packages or literature) gratefully accepted. S

Re: [R] Robust estimation of variance components for a nested design

that uses robust (eg Huber) treatment and returns robust estimates of variance. Nothing in my collection of R robust estimation packages (robust, robustbase and MASS being the obvious three) or on the Robust task view seems to cover this, though it's entirely possible I've missed something

[R] Robust estimation references

Hi, Can somebody help recommend some good introductory textbooks on robust estimation (graduate school level)? I found this one, but the reviews on this are quite diverse.