similar to: Regsubsets model selection

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 want to fit the best model again "manually"

Hi, I have a scatter plot of the variables GNI and Lifeexp (Gross National Income and Life Expectancy, both metric). So I plotted them and I want to add a regression line and a lowess line. I use lowess and not loess because I have missing values. My code: plot(GNI,Lifeexp) abline(lm(Lifeexp~GNI), col="red") y.loess<-loess(Lifeexp~GNI,na. action = na.exclude)

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="exhaustive") x is a data.frame with 40 variables and 277

Hi, does anyone know if there is a way to easily extract p-values from the regsubsets() function? Thanks, James Stegen p.s. this is a reposting due to me not putting in a useful subject heading... -- 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

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

Hello, I have encountered 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,

Hi R-list members, Could somebody explain to me the meaning of the '.' in the formula SumTL~. below? I could not find it in the help pages. I'm guessing it is substituted by v1+v2+v3+.. for all independent variables vi. Furthermore, I would like to add interaction effects to the model, is this also possible with the '.'? > library(leaps) >

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 =

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 is given in Ramsey and Schafer's, The Statistical Sleuth. I assume

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 constrain the model search so that "r"s and

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

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 following questions: 1. What should I do to get the statistics

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:

Hello I am trying to use all 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

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 Laboratoire de Biomecanique LBM - ENSAM - CNRS UMR 8005

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.acc.1 + RMSACC + RDI + RPSI + P.acc + cov.v + cov.a +

Hello dear R-help members, I recently became interested in using biglm with leaps, and found myself somewhat confused as to how to use the two together, in different 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

Hi i need to create a model from 250 + variables with high collinearity, and only 17 data points (p = 250, n = 750). I would prefer to use Cp, AIC, and/or BIC to narrow down 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

In my form I have these items: <%= select_year Date.today, :start_year => Schoolyear.get_startdate.year, :end_year => Schoolyear.get_enddate.year %> <%= select_month Date.today.month %> No matter what I do, in my controller I can''t seem to access the selected year and month. I have tried params[:month].to_s and also