similar to: leaps error

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,

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

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)

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:

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 =

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

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 +

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, I’d like to fit one GLM model for each possible combination of inputs (i.e. exhaustive search). The package leaps can help me to generate all possible variable subsets, but I’ll appreciate your guidance as of how to generate one model for each of those possible subsets. I’m new in R! Thanks in advance for your help. library(leaps) subsets <- regsubsets( y ~ . , data=freeny, nbest=100,

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

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:

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

Dear all, First of all - thanks to the R-users who replied my previous mail "Selecting Best Regression Equation". However, seems i've got some other problems now - My data in c:\leafbrn.txt file is- -------------------------------------- i x1 x2 x3 y 1 3.05 1.45 5.67 0.34 2 4.22 1.35 4.86 0.11 3 3.34 0.26 4.19 0.38 4 3.77 0.23 4.42 0.68 5 3.52 1.10 3.17 0.18 6 3.54 0.76 2.76

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

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) >

I have a patch for libspeex, which optimises some of the loops in vq_nbest and vq_nbest_sign that speeds up encoding - my results: test file: 10s wav file at 16000 Hz, mono encoding with wideband --quality 3, --comp 3 machine: PIII-900Mhz, 256MB RAM before: 2.78s after: 2.38s I'm still trying to grasp the code (I'm just a coder, no background in sound processing), and just optimised

I am trying to read and write database tables that have a date field in them. I am constructing a data.frame, then using dbWriteTable to create the table and dbReadTable to read it. >datatbl<-data.frame( dates, trialnum, fooddel, ethdel, trialtime, trialtype, deliveries, food, ethanol, fcumrec, dcumrec, rrf, rrd) >ifelse(startdate==filelist,

Hi: (Tried to find a bug report about this issue, but was unable to find it, let me know if this is a known issue) I have been working on an interface to highlight xyplot panels on mouse overs in JavaGD but I have stumbled with what seems to be a bug in trellis.focus. I am using JGR R 2.8 with lattice 0.17-15 Note: It's important to you use JGR to use the Java Graphics Device. *** To

Hi, ? Is there a fix for this issue??? ---> http://permalink.gmane.org/gmane.comp.audio.compression.speex.devel/2959 ? I am seeing the same thing when I compile speex in visualdsp ? These are the errors I get from using the assembly version of vq_nbest: ? ..\..\..\..\algorithms\voice\speex\src\vq.c [Error ea5004] "C:\Users\coder\AppData\Local\Temp\acc22e8547f000\acc22e8547f001.s":482

I am trying to replicate the following plot using Lattice: http://addictedtor.free.fr/graphiques/graphcode.php?graph=78 I'm having trouble with the lattice equivalent of the "oma" (outside margin) setting. I've been all through the Lattice documentation and others and also searched the lists. Below is sample code that demonstrates where I'm at (it should paste