search for: hasty

This works: > model.matrix(~I(pos>3),data=data.frame(pos=c(1:5))) (Intercept) I(pos > 3)TRUE 1 1 0 2 1 0 3 1 0 4 1 1 5 1 1 attr(,"assign") [1] 0 1 attr(,"contrasts") attr(,"contrasts")$"I(pos > 3)" [1] "contr.treatment"

Does anyone know whether there is an R version of the S-Plus software that can be downloaded from the website of the book Elements of Statistical Learning by Hastie, Tibshirani and Friedman? Rob Potharst -- ********************************************************** Dr. Rob Potharst Lecturer in Computer Science Erasmus University email: potharst at few.eur.nl P.O. Box 1738

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 hastie at stanford.edu Professor, Department of Statistics, Stanford University Phone:

I have contributed a "gam" library to CRAN, which implements "Generalized Additive Models". This implementation follows closely the description in the GAM chapter 7 of the "white" book "Statistical Models in S" (Chambers & Hastie (eds), 1992, Wadsworth), as well as the philosophy in "Generalized Additive Models" (Hastie & Tibshirani 1990,

I have contributed a "gam" library to CRAN, which implements "Generalized Additive Models". This implementation follows closely the description in the GAM chapter 7 of the "white" book "Statistical Models in S" (Chambers & Hastie (eds), 1992, Wadsworth), as well as the philosophy in "Generalized Additive Models" (Hastie & Tibshirani 1990,

Hola a todos, Gracias por avisar Carlos. Intentaré formar un grupo en Logroño. Belén Cillero Jiménez Técnico de Estadística Instituto de Estadística de La Rioja bcillero en larioja.org o?s?? ol ??d???s s???? ou ,so?u??s?p sop??lns?? s??snq ?S ________________________________________ De: r-help-es-bounces en r-project.org [r-help-es-bounces en r-project.org] en nombre de r-help-es-request

Yo me he apuntado y me parece bien tanto la idea de reunirse, como la de comentar a través de la lista. >________________________________ > De: "r-help-es-request@r-project.org" <r-help-es-request@r-project.org> >Para: r-help-es@r-project.org >Enviado: Viernes 10 de enero de 2014 12:00 >Asunto: Resumen de R-help-es, Vol 59, Envío 5 > > >Envíe los

Like many, I am sure, I get R-Help in digest form. Its easy enough to browse the subject lines, but then if an entry interests you, you have to embark on this tedious search or scroll to find it. It would be great to have a "clickable" digest, where the topics list is a set of pointers, and clicking on a topic takes you to that entry. I can think of at least one way to do this via

Is there any place where the Chambers and Hastie 1993 Statistical Models in S data sets can be found? Thank you very much. Peter B. -- Peter B. Mandeville mandevip at deimos.tc.uaslp.mx Jefe del Depto. de Inform?tica y Bioestad?stica rpe1531 at pasteur.fmed.uaslp.mx Facultad de Medicine Tel: 48 26-23-45 ext. 232 Universidad Aut?noma de San

Yo estoy esperando que empiece... Me parece fenomenal utilizar la lista, si al resto de gente (no apuntados) no le parece que le damos mucho la lata... Un saludo. Isidro > -----Mensaje original----- > De: r-help-es-bounces en r-project.org [mailto:r-help-es-bounces en r- > project.org] En nombre de Carlos J. Gil Bellosta > Enviado el: viernes, 10 de enero de 2014 11:18 > Para:

This update adds an intercept option (by popular request) - now one can fit a model without an intercept Glmnet is a package that fits the regularization path for a number of generalized linear models, with with "elastic net" regularization (tunable mixture of L1 and L2 penalties). Glmnet uses pathwise coordinate descent, and is very fast. The current list of models covered are:

This update adds an intercept option (by popular request) - now one can fit a model without an intercept Glmnet is a package that fits the regularization path for a number of generalized linear models, with with "elastic net" regularization (tunable mixture of L1 and L2 penalties). Glmnet uses pathwise coordinate descent, and is very fast. The current list of models covered are:

Hola, Yo también estoy interesado en el curso pero no me he apuntado nunca a un MOOC y no sé muy bien su funcionamiento. ¿Es gratuito?, ¿para apuntarme simplemente me registro en su web y ya está?. Muchas gracias por toda la información. Saludos, Guillermo > Hola a todos: > >

Hola, ¿qué tal? Sabréis que en unos días comienza un MOOC de Hastie y Tibshirani, https://class.stanford.edu/courses/HumanitiesScience/StatLearning/Winter2014/about basado en el libro "An Introduction to Statistical Learning, with Applications in R". Se me ocurre lo siguiente: 1) Montar un grupo de estudio en Madrid de manera que podamos reunirnos periodicamente (¿semanalmente?

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 developments in internet technology, genomics and other high-tech industries, we rely increasingly more on data

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 and prediction. With the rapid developments in internet technology, genomics and other high-tech industries, we

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 developments in internet technology, genomics and other high-tech industries, we rely

Hello list, I've been searching around trying to find whether somebody has written such a package of least angle regression on generalized linear models, like what Lasso2 package does. The extension to generalized linear models is briefly discussed in the comment by D. Madigan and G. Ridgeway. Is such a package available? Thanks, Mike [[alternative HTML version deleted]]

...ummarized here[a]. [a] http://www.jiscmail.ac.uk/help/policy/copyright.htm Has it been changed to the following? http://www.jiscmail.ac.uk/policyandsecurity/copyrightissues.html (2) Regarding the following extract `If you feel insulted by some response to a post of yours, don't make any hasty response in return - you're as likely as not to regret it.' wouldn't someone who is `as likely as not to regret it' be indifferent between sending a hasty response and not sending a hasty response? The intent is perfectly clear but perhaps `you're _more_ likely than not' is...

Hola. Yo también me he apuntado al curso, pero no sé si hay alguien más en Córdoba. Por mi encantado de montar un grupo de estudio aquí o incluso en Granada, que sé que hay unos cuantos usuarios de R allí.. Si alguien por Andalucía está interesado en este curso le animo a que nos pongamos en contacto y ver como podemos organizarnos. Un saludo. José Luis Cañadas El 10/01/14 11:17, Carlos J.