search for: regsubset

...wn the number of variables, and then use VIF to choose a model without collinearity (if possible). I realize that having a huge p and small n is going to give me extreme linear dependency problems, but I *think* these model selection criteria should still be useful? I have currently been running regsubsets for over a week with no results. I have no idea if R is still working, or if the computer is hung. I ran regsubsets on a smaller portion of the data, also with linear dependency problems, and got results. However, the hourglass continues its endless spiraling with the full dataset. I am running t...

Hi, I'm new to R and this mailing list, so I will attempt to state my question as appropriately as possible. I am running R version 2.7 with Windows XP and have recently been exploring the use of the function regsubsets in the leaps package in order to perform all-subsets regression. So, I'm calling the function as: sub=regsubsets(X,Y,nbest=5,nvmax=maxnv,method="exhaustive",really.big=F) I'm dealing with 14 observations and 23 variables and I'm aware of the linear dependencies that ar...

Hi all I am hoping this is just a minor problem, I am trying to implement a best subsets regression procedure on some ecological datasets using the regsubsets function in the leaps package. The dataset contains 43 predictor variables plus the response (logcount) all in a dataframe called environment. I am implementing it as follows: library(leaps) subsets<-regsubsets(logcount~.,data=environment,nvmax=10,nbest=2,really.big=FALSE,method="exhaus...

...ent settings. I couldn't find any example codes for the leaps() package (except for in the help file, and the examples there are not as rich as they could be). That is why I turn to you in case you could share some good tips and examples of code on how to use the leaps package (especially the regsubsets command) The problem that drives me to ask this is: how to use the regsubsets() command to immulate a forward model selection procedure on a regressions problem ? I attach below a few direction dear Thomas has already wrote to me on the subject, and any help would be very welcomed: *me:* I fee...

Hello, I am using the 'regsubsets' function (from leaps package) to get the best linear models to explain 1 variable from 1 to 5 explanatory variables (exhaustive search). Is there anyone who can tell me on which criterion is based the 'regsubsets' function ? Thank you. samuel Samuel BERTRAND Doctorant Laborato...

Hi, I want to make model selection with regsubsets. My code is: a<-regsubsets(Gesamt ~ CommunistSocialist + CountrySize + GNI + Lifeexp + Schoolyears + ExpMilitary + Mortality + PopPoverty + PopTotal + ExpEdu + ExpHealth, data=olympiadaten, nbest=2) summary(a) plot(a,scale="adjr2") (output attached) The problem is now, that I wan...

Dear R-help, I have used the regsubsets function from the leaps package to do subset selection of a logistic regression model with 6 independent variables and all possible ^2 interactions. As I want to get information about the statistics behind the selection output, I?ve intensively searched the mailing list to find answers to foll...

The function 'regsubsets' appears to calculate a BIC value that is different from that returned by the function 'BIC'. The latter is explained in the documentation, but I can't find an expression for the statistic returned by 'regsubsets'. Incidentally, both of these differ from the BIC that i...

Hi, I have 12 independent variables and one dependent variable. Now I want to select the best adj. R squared model by using the regsubsets command, so I code: > plot(regsubsets(Gesamt ~ CommunistSocialist + CountrySize + GNI + Lifeexp + Schoolyears + ExpMilitary + Mortality + + PopPoverty + PopTotal + ExpEdu + ExpHealth, data=olympiadaten, nbest=1, nvmax=12), scale='adjr2') Then I get the picture I attached. The proble...

Hi, I'd like to run regsubsets for model selection by exhaustive search. I have a list with 20 potential explanatory variables, which represent the real and the imaginary parts of 10 "kinds" of complex numbers: x <- list(r1=r1, r2=r2, r3=r3, ..., r10=r10, i1=i1, i2=i2, i3=i3, ..., i10=i10) Is there an easy way to...

...ll subsets regression on a test dataset consisting of 11 trails and 46 potential predictor variables. I would like to use Mallow's Cp as a selection criterion. The leaps function would provide the required output but does not work with this many variables (see below). The alternative function regsubsets should be used, but I am not able to define the function in such a way that is gives satisfactory results. library(leaps) data <- read.table('C:/test_plot_sum2.txt', header = TRUE) attach(data) nox <- data[,1] cnt <- data[,2] vars <- data[,3:48] leaps.setup(x = vars...

Hi, does anyone know if there is a way to easily extract p-values from the regsubsets() function? Thanks, James Stegen -- James C. Stegen NSF Postdoctoral Fellow in Bioinformatics University of North Carolina Chapel Hill, NC 919-962-8795 stegen at email.unc.edu http://www.unc.edu/~stegen/index.html

How would I rewrite my code so that I can implement the use of multicore on an Rstudio server to run regsubsets using the "exhaustive" method? The data has 1200 variables and 9000 obs so the code has been shortened here: model<-regsubsets(price~x + y + z + a + b + ...., data=sample, nvmax=500, method=c("exhaustive")) Our server is a quad core 7.5 gb ram, is that enough for a...

Dear List members I am using the regsubsets function to select a few predictor variables using Mallow's Cp: > sel.proc.regsub.full <- regsubsets(CO2 ~ v + log(v) + v.max + sd.v + tad + no.stops.km + av.stop.T + a + sd.a + a.max + d + sd.d + d.max + RPA + P + perc.stop.T + perc.a.T + perc.d.T + RPS + RPSS + sd.P.acc + P.dec + da....

Hi, I'm using regsubsets and it works fine when nvmax = 4. However when I go for any value above 4, I get the error: Warning message: XHAUST returned error code -999 in: leaps.exhaustive(a, really.big = really.big) I'm calling regsubsets as: lp <- regsubsets(x,y,nbest=1,nvmax=5,intercept=T,really.big=T, method=&...

...ed a problem which may be arising from details of my data and or the statistics I am trying to do, or may be arising due to the way leaps works internally. Unfortunately, I am not yet savvy enough to tell why. I can say that this statement works (or at least works to the degree I expect): b <- regsubsets(FUND~.,data=all, intercept=TRUE, nbest=1, nvmax=8, really.big=T, method="forward") It does produce a warning: Warning message: In leaps.setup(x, y, wt = wt, nbest = nbest, nvmax = nvmax, force.in = force.in, : 2 linear dependencies found But I can appreciate that and can reduce my...

...in writing some model selection functions (for linear regression models, as a start), which incorporate the PRESS criterion since it, to my knowledge, is not currently implemented in any available model selection procedure. I thought it would be simplest to build on already existing functions like regsubsets in package leaps. It's easy enough to calculate the PRESS criterion for a fitted lm object, but I'm having trouble deciphering the structure of the regsubsets objects that leaps works with. Is there any way to calculate press from a regsubsets? Or, to put it another way, can I get the r...

Hi Folks, I've got a question concerning the calculation of the Schwarz-Criterion (BIC) done by summary.regsubsets() of the leaps-package: Using regsubsets() to perform subset-selection I receive an regsubsets object that can be summarized by summary.regsubsets(). After this operation the resulting summary contains a vector of BIC-values representing models of size i=1,...,K. My problem is that I can'...

Hi, I would like to perform a forward selection procedure on a data set with 6 observations and 10 predictors. I tried to run it with regsubsets (I set nvmax=number of observations) but I keep getting these warning messages: Warning messages: 1: 5 linear dependencies found in: leaps.setup(x, y, wt = weights, nbest = nbest, nvmax = nvmax, 2: nvmax reduced to 5 in: leaps.setup(x, y, wt = weights, nbest = nbest, nvmax = nvmax, I thi...