[R] [R-pkgs] New version 0.9-7 of lars package

problems, or old ones not yet repaired. Trevor Hastie Trevor Hastie [EMAIL PROTECTED] Professor Chair, Department of Statistics, Stanford University Phone: (650) 725-2231 (Statistics

Re: [R] contingency table analysis; generalized linear model

data in the right way. Trevor Hastie --- Trevor Hastie [EMAIL PROTECTED] Professor Chair, Department of Statistics, Stanford University Phone: (650) 725-2231 (Statistics) Fax: (650

[R] Statistical Learning and Datamining Course

Short course: Statistical Learning and Data Mining II: tools for tall and wide data Trevor Hastie and Robert Tibshirani, Stanford University Sheraton Hotel, Palo Alto, California, April 3-4, 2006. This two-day course gives a detailed overview of statistical models for data

[R] Data Mining Course

Short course: Statistical Learning and Data Mining II: tools for tall and wide data Trevor Hastie and Robert Tibshirani, Stanford University Sheraton Hotel, Palo Alto, California, April 3-4, 2006. This two-day course gives a detailed overview of statistical models for data

[R] Age of an object?

It would be nice to have a date stamp on an object. In S/Splus this was always available, because objects were files. I have looked around, but I presume this information is not available. Trevor Hastie

[R] [R-pkgs] glmpath: L1 regularization path for glms

example with 5000 variables and 100 observations, 11 seconds cpu time. Currently glmpath implements binomial, poisson and gaussian families. Mee Young Park and Trevor Hastie --- Trevor Hastie

Re: [R] step.gam- question

] -- Trevor Hastie [EMAIL PROTECTED] Professor, Department of Statistics, Stanford University Phone: (650) 725-2231 (Statistics) Fax: (650) 725-8977 (650) 498-5233

[R] Data Modeling Short Course

Short course: Statistical Learning and Data Mining II: tools for tall and wide data Trevor Hastie and Robert Tibshirani, Stanford University The Conference Center at Harvard Medical School Boston, MA, Oct 31-Nov 1, 2005 This is a *new* two-day course on statistical models

[R] Attractive position at Stanford for statistician into computing

are at the cutting edge of technology. For more details, see the link on the department web page: http://www-stat.stanford.edu/cssad.html Trevor Hastie Trevor Hastie [EMAIL PROTECTED

[R] new data mining course

Short course: Statistical Learning and Data Mining II: tools for tall and wide data Trevor Hastie and Robert Tibshirani, Stanford University The Conference Center at Harvard Medical School Boston, MA, Oct 31-Nov 1, 2005 This is a *new* two-day course on statistical models

[R] Digest reading is tedious

, and clicking on a topic takes you to that entry. I can think of at least one way to do this via web pages, but I bet those with more web skills than me can come up with an elegant solution. ---   Trevor Hastie

[R] Statistical Learning and Data Mining Course

Short course: Statistical Learning and Data Mining Trevor Hastie and Robert Tibshirani, Stanford University Sheraton Hotel, Palo Alto, California February 24 25, 2005 This two-day course gives a detailed overview of statistical models for data mining, inference and prediction. With the rapid

[R] Statistical Learning and Data Mining course

Short course: Statistical Learning and Data Mining Trevor Hastie and Robert Tibshirani, Stanford University Georgetown University Conference Center Washington DC September 20-21, 2004 This two-day course gives a detailed overview of statistical models for data mining, inference

[R] [R-pkgs] gam --- a new contributed package

a function that computes exact standard errors along the lines described in the GAM book page 127. Trevor Hastie Trevor Hastie [EMAIL PROTECTED] Professor, Department of Statistics

[R] Statistical Learning and Data Mining Course

Short course: Statistical Learning and Data Mining Trevor Hastie and Robert Tibshirani, Stanford University Georgetown University Conference Center Washington DC September 20-21, 2004 This two-day course gives a detailed overview of statistical models for data mining, inference

[R] svmpath: fitting the entire SVM regularization path

problems, with up to 1000 observations. The current version is not industry ready; occasionally it will run into situations where the steps are too small, leading to machine zero situations. Usually increasing the parameter eps from its default 1e-10 will avoid this. Trevor Hastie

[R] problem with model.matrix

(pos 3) [1] contr.treatment This does not: model.matrix(~I(pos3),data=data.frame(pos=c(1:2))) Error in contrasts-(`*tmp*`, value = contr.treatment) : contrasts can be applied only to factors with 2 or more levels Trevor

[R] Re: missing values for mda package

no missing values. The spam data were used to demonstrate mars in Elements of Statistical Learning The spam data has no missing values, and can be obtained from http://www-stat.stanford.edu/~tibs/ElemStatLearn/ Trevor Hastie Trevor

[R] Statistical Learning and Datamining course based on R/Splus tools

Short course: Statistical Learning and Data Mining Trevor Hastie and Robert Tibshirani, Stanford University Sheraton Hotel Palo Alto, CA Feb 26-27, 2004 This two-day course gives a detailed overview of statistical models for data mining, inference and prediction. With the rapid

[R] Re: Logistic Regression

://www-stat.stanford.edu/~hastie/Papers/margmax1.ps Trevor Hastie [EMAIL PROTECTED] Professor, Department of Statistics, Stanford University Phone: (650) 725-2231 (Statistics)Fax