[R] ungrouped data for multinomial regression
Thanks for helping me out with the thing of quotation marks. I finally could save time running programs at the university and home. One additional question for all of you. I'm starting to be familiar with multinomial regression models. Actually I'm doing some exercise with the pneumo data that appears in Faraway library. The database has 24 observations and I want to study the probability of getting sick according with the number of years working at a coal mine. Here is the issue. For modelling that response what I need to include in the model is something similar at what is produced by: xtabs(Freq~year+status). This table provided me the proportions of people sick according with years worked and severity of the disease. The question is: do this imply that I need to transform my data previously to run the regression? how? Thanks in advance. __ R-help@r-project.org 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.
[R] use of quotation marks
Dear R Users. I just discovered today a problem in the use of quotation marks when I'm doing some programs in R. I'm using windows vista environment. The programs that I wrote in the University, made in Windows XP machines run perfectly, but when I run those in my laptop with VISTA, there are many errors. Those errors are due to the type of quotation marks. In the university the quotation marks appear inclined (talking about position), but in Vista quotation marks are totally vertical. So my question is how to avoid this issue? Is there an specific font format that I need to use to avoid those problems??? Thanks in advance for the help. __ R-help@r-project.org 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.
[R] prediction with ridge regression
I'm running a ridge regression of Y over 8 explanatory variables. The selection of lambda gave me a value of 1 as the minimum value to be added for bias. I got the coeficients for this new regression. The thing is that I have 8 new values for explanatory variables that are needed in order to predict the response using the ridge regression already ran. Since I'm not very familiar with the way R functions I will explain what I did: 1. New values were inserted: nx=c(64.8,263.7,181.08,178.56,91.44,35.64,40.95,38.79) each corresponds to a new value for each of the explanatory variables. Doubt: it is ok on this way or do I need to put like data frame? x0 = data.frame(x1=64.8,x2=263.7,x3=181.08,x4=178.56,x5=91.44,x6=35.64,x7=40.95,x8=38.79) 2. Prediction with the original LM model was done using the command: predict(spos.mod,x0), where spos.mod is the linear model and x0 is the new data (data.frame) 3. Not clear how to do the same with ridge, in order to compare the previous prediction with the one from the new model (spos.ridge) Any help is really appreciated. __ R-help@r-project.org 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.
Re: [R] use of sequence on ridge regression
Sorry to bother with this topic, but I'm still not clear about the meaning of the value set that is used on lambda values. Is there a correct way of doing that? My doubt is how to choose those 3 values that appear in the example. Thanks. On Wed, May 7, 2008 at 9:29 AM, Prof Brian Ripley <[EMAIL PROTECTED]> wrote: > On Wed, 7 May 2008, Rodrigo Briceño wrote: > > > > Nice to meet you Brian. The question is about the numbers that appears > > after lambda (0,0, 0.1, 0.0001). I know that seq is a set of values used > > for testing which value fits best. But I'm not sure if I need to put > > whatever I think or what. I tried also with a set of 5 values and I get > > an error. Is there a maximum allowed? > > > > So you mean the set of values of lambda? It is just a set to be use for a > plot and for searching in the select() methods. > > There is an R function called sequence(), and it is not the same as seq(). > > > > > > > > plot(lm.ridge(hipcenter ~ .,seatpos, lambda = seq(0,0.1,0.001))) > > select(lm.ridge(hipcenter ~ ., seatpos,lambda = seq(0,0.1,0.001))) > > > > __ > > > > Rodrigo Briceño > > Project Manager > > Sanigest Internacional > > > > +506 22-91-12-00 ext. 113 Oficina Costa Rica > > +506 22-32-08-30 Fax > > +506 88-86-11-77 Celular > > [EMAIL PROTECTED] > > www.sanigest.com > > > > MSN: [EMAIL PROTECTED] > > SKYPE: rbriceno1087 > > > > _ > > > > This communication contains legal information which is privileged and > > confidential. It is for the exclusive use of the address and > > distribution, dissemination, copying or use by others is strictly > > prohibited. If you have received this communication by error, please > > delete the original message and e-mail us. > > > > > > Esta comunicación contiene información legal privilegiada y confidencial > > para el uso exclusivo del destinatario. La distribución, diseminación, > > copia u otro uso por terceras personas es estrictamente prohibida. Si > > usted ha recibido esta comunicación por error, le rogamos borrar el > > mensaje original y comunicárnoslo a esta misma dirección. > > > > > > > > Prof Brian Ripley wrote: > > What do you mean by 'the sequence option'? > > > > The authot of lm.ridge > > > > On Wed, 7 May 2008, Rodrigo Briceño wrote: > > > >Dear R users. I have a doubt about the use of the > >sequence option on > >Ridge regression. I'm trying to understand the > >use of this option when > >variables are highly linear correlated. I'm > >running a model where the > >variables HtShoes and Ht have high VIF values. My > >program is written > >below, but I'm not sure about the correct way of > >using the sequence > >option: > > > >library (faraway) > >data (seatpos) > >attach (seatpos) > >spos.mod <- lm(hipcenter ~ .,seatpos) summary > >(spos.mod) > >library(MASS) > >lm.ridge(hipcenter ~ .,seatpos) > >plot(lm.ridge(hipcenter ~ .,seatpos, lambda = > >seq(0,0.1,0.001))) > >select(lm.ridge(hipcenter ~ ., seatpos,lambda = > >seq(0,0.1,0.001))) > > > >Any advice will be appreaciated. Rodrigo B. > > > >__ > >R-help@r-project.org 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. > > > > > > > > > > > > > -- > Brian D. Ripley, [EMAIL PROTECTED] > Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ > University of Oxford, Tel: +44 1865 272861 (self) > 1 South Parks Road, +44 1865 272866 (PA) > Oxford OX1 3TG, UKFax: +44 1865 272595 __ R-help@r-project.org 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.
Re: [R] use of sequence on ridge regression
Nice to meet you Brian. The question is about the numbers that appears after lambda (0,0, 0.1, 0.0001). I know that seq is a set of values used for testing which value fits best. But I'm not sure if I need to put whatever I think or what. I tried also with a set of 5 values and I get an error. Is there a maximum allowed? plot(lm.ridge(hipcenter ~ .,seatpos, lambda = seq(0,0.1,0.001))) select(lm.ridge(hipcenter ~ ., seatpos,lambda = seq(0,0.1,0.001))) __ *Rodrigo Briceño* Project Manager Sanigest Internacional +506 22-91-12-00 ext. 113 * Oficina* *Costa Rica* +506 22-32-08-30 *Fax *+506 88-86-11-77* Celular** [EMAIL PROTECTED] <mailto:[EMAIL PROTECTED]> www.sanigest.com <http://www.sanigest.com/> MSN: [EMAIL PROTECTED] <mailto:[EMAIL PROTECTED]> SKYPE: rbriceno1087 _ This communication contains legal information which is privileged and confidential. It is for the exclusive use of the address and distribution, dissemination, copying or use by others is strictly prohibited. If you have received this communication by error, please delete the original message and e-mail us. Esta comunicación contiene información legal privilegiada y confidencial para el uso exclusivo del destinatario. La distribución, diseminación, copia u otro uso por terceras personas es estrictamente prohibida. Si usted ha recibido esta comunicación por error, le rogamos borrar el mensaje original y comunicárnoslo a esta misma dirección. Prof Brian Ripley wrote: > What do you mean by 'the sequence option'? > > The authot of lm.ridge > > On Wed, 7 May 2008, Rodrigo Briceño wrote: > >> Dear R users. I have a doubt about the use of the sequence option on >> Ridge regression. I'm trying to understand the use of this option when >> variables are highly linear correlated. I'm running a model where the >> variables HtShoes and Ht have high VIF values. My program is written >> below, but I'm not sure about the correct way of using the sequence >> option: >> >> library (faraway) >> data (seatpos) >> attach (seatpos) >> spos.mod <- lm(hipcenter ~ .,seatpos) summary (spos.mod) >> library(MASS) >> lm.ridge(hipcenter ~ .,seatpos) >> plot(lm.ridge(hipcenter ~ .,seatpos, lambda = seq(0,0.1,0.001))) >> select(lm.ridge(hipcenter ~ ., seatpos,lambda = seq(0,0.1,0.001))) >> >> Any advice will be appreaciated. Rodrigo B. >> >> __ >> R-help@r-project.org 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. >> > [[alternative HTML version deleted]] __ R-help@r-project.org 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.
[R] use of sequence on ridge regression
Dear R users. I have a doubt about the use of the sequence option on Ridge regression. I'm trying to understand the use of this option when variables are highly linear correlated. I'm running a model where the variables HtShoes and Ht have high VIF values. My program is written below, but I'm not sure about the correct way of using the sequence option: library (faraway) data (seatpos) attach (seatpos) spos.mod <- lm(hipcenter ~ .,seatpos) summary (spos.mod) library(MASS) lm.ridge(hipcenter ~ .,seatpos) plot(lm.ridge(hipcenter ~ .,seatpos, lambda = seq(0,0.1,0.001))) select(lm.ridge(hipcenter ~ ., seatpos,lambda = seq(0,0.1,0.001))) Any advice will be appreaciated. Rodrigo B. __ R-help@r-project.org 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.
[R] ridge regression
Thanks to all of you that helped me with the issues of bootstrapping and downloading packages to a local disk. As an starter I'm in the lower side of the learning curve, but this R software is awesome. What I like most is this kind of forums when people share their problems and we can find solutions. My new inquiry is short: do any of you have some example (besides the one that appears in help) about a simple ridge regression application in R? I'm trying to figure out how the program estimates the constant value that is most appropiate to run regression and how can I see that value in the plot. My operative system: windows XP, running R 2.6.2 Thanks to all __ R-help@r-project.org 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.
[R] ridge regression
Thanks to all of you that helped me with the issues of bootstrapping and downloading packages to a local disk. As an starter I'm in the lower side of the learning curve, but this R software is awesome. What I like most is this kind of forums when people share their problems and we can find solutions. My new inquiry is short: do any of you have some example (besides the one that appears in help) about a simple ridge regression application in R? I'm trying to figure out how the program estimates the constant value that is most appropiate to run regression and how can I see that value in the plot. My operative system: windows XP, running R 2.6.2 Thanks to all __ R-help@r-project.org 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.
[R] downloading packages at local disk
Hi again R users. I was reviewing the manual of R about how to install packages using the GUI and it's corresponding menu packages. My question is how to download a specific set of packages in order to install them in a computer that doesn't have internet access. Is there a web page where I can search those packages? Basically I'm trying to copy in a flash drive the packages MASS, BOOT and CAR. Thanks for your help. Rodrigo Briceño __ R-help@r-project.org 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.
[R] Fwd: my first post to the list
Hello R-listers! My first post to the list is a very simple one for
those who use the software continuosly. I am trying to understand the
fixed-x resampling and random-x-resampling method proposed by Fox
about Bootstrapping. The doubt that I have is on the side of the model
run in one of the functions expressed for fixed-x resampling. What I
don't understand is: X=model.matrix, and the -1 under mod= rlm. Please
see below:
#fixed x-resampling
fit <- fitted(mod.duncan.hub)
e <- residuals(mod.duncan.hub)
X <- model.matrix(mod.duncan.hub)
boot.huber.fixed <- function(data, indices, maxit=20){
y <- fit + e[indices]
mod <- rlm(y ~ X - 1, maxit=maxit)
coefficients(mod)
}
duncan.fix.boot <- boot(Duncan, boot.huber.fixed, 1999, maxit=100)
duncan.fix.boot
I just need a quick explanation about WHAT the functions mean or do in
this context.
Thanks
__
R-help@r-project.org 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.
[R] my first post to the list
Hello R-listers! My first post to the list is a very simple one for those
who use the software continuosly. I am trying to understand the fixed-x
resampling and random-x-resampling method proposed by Fox about
Bootstrapping. The doubt that I have is on the side of the model run in one
of the functions expressed for fixed-x resampling. What I don't understand
is: X=model.matrix, and the -1 under mod= rlm. Please see below:
#fixed x-resampling
fit <- fitted(mod.duncan.hub)
e <- residuals(mod.duncan.hub)
X <- model.matrix(mod.duncan.hub)
boot.huber.fixed <- function(data, indices, maxit=20){
y <- fit + e[indices]
mod <- rlm(y ~ X - 1, maxit=maxit)
coefficients(mod)
}
duncan.fix.boot <- boot(Duncan, boot.huber.fixed, 1999, maxit=100)
duncan.fix.boot
I just need a quick explanation about WHAT the functions mean or do in this
context.
Thanks
[[alternative HTML version deleted]]
__
R-help@r-project.org 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.
