similar to: plotting results from leaps library

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

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

Dear all I am supposed to use Mallow's Cp creterion to select a model which require a "leaps" package. the version right now I am using is R 1.7.1(os:windows), the "leaps" package is not included. please let me know how and where can I get this package and add it to the current version, any caution on adding this package is highly appreciated. thank you best

Hello, Newbie here, be gentle ;) I have a reference book that discusses regression model selection using several methods - what they call 'Forward Model Selection' i.e. add one variable at a time and examining R, R^2, Mallow's C-p value, etc., 'Backward Model Selection' i.e. starting out with all the variables included and then remove them one at a time, and examining for

Dear list, given this formula: > fmla <- formula(y1 ~ spp1 + spp2 + spp3 + spp5) > fmla[[3]] spp1 + spp2 + spp3 + spp5 is this the intended behaviour of as.character: > as.character(fmla[[3]]) [1] "+" "spp1 + spp2 + spp3" "spp5" ? Where does the extra "+" come from? > as.character(fmla) [1] "~"

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

Hi I'm having a problem with model.frame, encapsulated in this example: y1 <- matrix(c(3,1,0,1,0,1,1,0,0,0,1,0,0,0,1,1,0,1,1,1), nrow = 5, byrow = TRUE) y1 <- as.data.frame(y1) rownames(y1) <- paste("site", 1:5, sep = "") colnames(y1) <- paste("spp", 1:4, sep = "") y1 model.frame(~ y1) Error in model.frame(formula, rownames,

I'm interested 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

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)

Dear List, I have the following function: coca <- function(x, ...) { if(is.null(class(x))) class(x) <- data.class(x) UseMethod("coca", x) } and a default method coca.default <- function(x, y, method = c("predictive", "symmetric"), reg.method = c("simpls", "eigen"), weights = NULL,

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

Colleagues, please help me with the simple question. How can I find R2 and p while doing best subsets regression? Also how can I see B and p for coefficients? Maybe you can advice me detailed manual, because in manual for the package this is not described. Thank you

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

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

Hi, I'm using regsubsets from the leaps package to select subsets of variables. I'm calling the function as lp <- regsubsets(x,y,nbest=5,nvmax=9) Then I call plot to see which variables turned up in the models. I use the R^2 scale and see my best model had a R^2 of 0.62. However when I make a linear model using lm() with the same x my R^2 is 0.45. Should'nt I be seeing the

Hi everybody, Excuse me for this silly question, but after searching the help archives I'm still unable to find my way to read the source code of the "biplot" function in R. I have installed the mvbutils package, and tried: > fixr(biplot) which only gives me: function (x, ...) UseMethod("biplot") with no further details.... I'd like to read the code to see if

where is the cook-distance in R? i can't find it!please help me!

I am attempting to use R through WinEdt. I installed the SWinRegistry package and it seems to install fine. But when I type: > library(RWinEdt) I get: Error in library(WinEdt) : there is no package called 'RWinEdt' I am running Windows XP and R 1.8.1 The SWinRegistry is correctly named as well that is it is named: SWinRegistry_0.3-3.zip, which I know caused

Hi! Is there a way to get biplot and identify to work togheter. Having the output of prcomp I would like to draw a biplot that. Instead of plotting the sample (row-names) names plots some "pch" symbols. (thats easy with xlabs) But now I would like to add using identify the names to only some of the points. I have noticed that both biplot.prcomp and biplot.default does a lot of