similar to: Leaps and bound

Dear R users, I have to use a R function which call a Fortran code: result <- .Fortran("Name", arguments) I have the following error message: R> Error in .Fortran("Name", arguments .... R> C/Fortran function name not in load table Any ideas? I am working on PC with R 1.4.0 (loading from R Binaries, Windows, Base, SetupR.exe installation with all the

Dear friends. On the Bayesian averaging homepage http://www.research.att.com/~volinsky/bma.html I found some S code some of which perhaps may run in R. There was a call to an algorithm possibly within S but not supported by R 64.1: "leaps and bounds". I guess it is a minimization step. Can anyone clarify the algorithm and perhaps even give a pointer to some code ? I guess this may be

HI, List I want to know weather any body has used BMA Package for model averaging for prediction of future values.....What are the paprmeters we have to suplly to the model. Any script for the same. thanks in advance ANIL KUMAR( METEOROLOGIST) LRF SECTION NATIONAL CLIMATE CENTER ADGM(RESEARCH) INDIA METEOROLOGICAL DEPARTMENT SHIVIJI NAGAR PUNE-411005 INDIA MOBILE +919422023277

Hello everyone, I am searching for a covariate selection procedure in a cox model formulated as a counting process. I use intervals, my formula looks like coxph(Surv(start,stop,status)~ x1+x2+...+cluster(id),robust=T) where id is a country code (I study occurence of civil wars from 1962 to 1997). I'd like something not based on p-values, since they have several flaws for this purpose. I turned

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

Hullo, I am trying to use the leaps package, & keep getting the following error: Error in leaps.setup(x, y, wt = wt, nbest = nbest, nvmax = NCOL(x) + int, : y and x different lengths My data set is attached below. I am rather new to R, & would appreciate any help that could be given. Thanks. http://n4.nabble.com/file/n1755941/lr04.txt lr04.txt -- View this message in context:

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

Dear UseRs, I wanted to know that i have been using "leaps" for the proper models selection for my work. I read so many articles from internet which categorically outlined that "leaps" command for model selection should never be used as its not efficient. Moreover, as a matter of fact, i personally noticed that the accuracy of "leaps" package is very much

Hi there, This problem has been dogging me for a bit, and I'm trying to figure out why. When running the the subsets function in the leaps library, R is giving me the following error message > lvodsub <- subsets(pred, resp$LVOD) Warning message: XHAUST returned error code -999 in: leaps.exhaustive(a, really.big = really.big) but this still happens if I add the really.big option:

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 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

I am generating a bunch of examples for my students and when I type R BATCH demo10.R (file demo10.R reproduced below) I get an error: ------------- Error message ------ > plot(mods$size,mods$Cp, + main="Cp versus talla modelos", + xlab=expression(p), + ylab=expression(C[p])) Error in plot.window(xlim, ylim, log, asp, ...) : need finite ylim values In

Hi, there, S+ has a function leaps which can be used for criterion based model selection. Is there an equivalent function in R? thanks in advance. Kenny Ye Assistant Professor Department of Applied Math and Statistics SUNY at Stony Brook Stony Brook, New York 11794-3600 (516)632 9344 -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read

Hi In trying to fit a linear model , I use the leaps() function to determine wich predictors I should include in my model. I would like to plot the Mallow's Cp criteria against p with the indexes of selected model variates as points labels Is there already such a function? (I could not find it) Thanks Anne [[alternative HTML version deleted]]

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 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)

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

Is there any plan to compile leaps library for windows? thanks. Kenny Kenny Ye Assistant Professor Department of Applied Math and Statistics SUNY at Stony Brook Stony Brook, New York 11794-3600 Phone (631)632-9344 Fax (631)632-8490 -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send

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, 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