[R] Logistic regression problem

I have a huge data set with thousands of variable and one binary variable. I know that most of the variables are correlated and are not good predictors... but... It is very hard to start modeling with such a huge dataset. What would be your suggestion. How to make a first cut... how to eliminate m

Re: [R] Moving windows solution

ply and the > three accompanying vignettes. > > > library(zoo) > > z <- zoo(1:10) > > rollapply(z, 3, sum) > >  2  3  4  5  6  7  8  9 >  6  9 12 15 18 21 24 27 > > On Sat, Sep 27, 2008 at 10:45 AM, milicic.marko <[EMAIL PROTECTED]> wrote: > > Is ther

[R] Moving windows solution

Is there an implementation of moving window functionality so I can apply any function while sliding trough window. 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-pr

[R] Programming chalange

Okay... I would like to have some elegant (writting generic R code) solution to do following. I have a dataset X1 X2 X3 X4 1 23 4 1 23 4 1 23 4 1 23 4 1 23 4 1 23 4 1 23 4 1 23 4 I would like to specify sometnig like this: windows <- c(3, 4); fun

[R] Inverting data frame...row wise

Hi, I have the data.frame with 4 columns. I simply want to invert dataset so that last row becomes first... I tried with rev(my_data-frame) but I got my columns inverted... not my rows Thanks __ R-help@r-project.org mailing list https://stat.ethz.ch/

Re: [R] Design lrm function

Thanks Frank. On Sep 20, 2:53 am, Frank E Harrell Jr <[EMAIL PROTECTED]> wrote: > milicic.marko wrote: > > Hi, > > > Is it possible to get ROC and accuracy ratio/gini straight out of the > > Design package? > > > Thanks > > The print method for lrm

[R] Design lrm function

Hi, Is it possible to get ROC and accuracy ratio/gini straight out of the Design package? 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

Re: [R] Discretize continous variables....

ted in terms > >> of the cube root of the predictor to avoid excess influence. > > >> Frank > > >>> Regarding question 2: I thought you mean that you want to reduce the > >>> number > >>> of levels (say 4) to a smaller number of levels (say 2

[R] Discretize continous variables....

Hi R helpers, I'm preparing dataset to fir logistic regression model with lrm(). I have various cointinous and discrete variables and I would like to: 1. Optimaly discretize continous variables (Optimaly means, maximizing information value - IV for example) 2. Regroup discrete variables to achie