similar to: Argument matching for primitives

Dear R community I have tried to run the diagnostics on my lm object with the gvlma package but it gave me an error with the following message: Non compatible arguments I post here my syntax and session info: RegreC3<-lm(Classification_Score~C3L+Age_+Dx,data=DB1)summary(RegreC3) library(gvlma)gvmodel <- gvlma(RegreC3) R version 2.13.1 (2011-07-08)Platform: i386-pc-mingw32/i386 (32-bit)

Hi, Using the example data from library(gvlma) library(gvlma) data(CarMileageData) CarMileageNew <- CarMileageData[,c(5,6,3)] ?lst1 <- list() ?y <- c("NumGallons", "NumDaysBetw") ?for(i in seq_along(y)){ ?lst1[[i]] <- gvlma(lm(get(y[i])~MilesLastFill,data=CarMileageNew)) ?lst1} pdf("gvlmaplot.pdf") ?lapply(lst1,plot) dev.off() You could also use

1) Packages to be used- For smaller datasets use these 1. CAR Package http://cran.r-project.org/web/packages/car/index.html 2. GVLMA Package http://cran.r-project.org/web/packages/gvlma/index.html 3. ROCR Package http://rocr.bioinf.mpi-sb.mpg.de/ 4. Relaimpo Package 5. DAAG package 6. MASS package 7. Bootstrap package 8. Leaps package Also see

The new version 0.7 of our RobASt-family of packages is available on CRAN for several days. As there were many changes we will only sketch the most important ones here. For more details see the corresponding NEWS files (e.g. news(package = "RobAStBase") or using function NEWS from package startupmsg i.e. NEWS("RobAStBase")). First of all the new package RobLoxBioC was

The new version 0.7 of our RobASt-family of packages is available on CRAN for several days. As there were many changes we will only sketch the most important ones here. For more details see the corresponding NEWS files (e.g. news(package = "RobAStBase") or using function NEWS from package startupmsg i.e. NEWS("RobAStBase")). First of all the new package RobLoxBioC was

I've uploaded a new version of "catspec" to CRAN. Catspec is for estimating certain "special categorical" models. It also contains "ctab", a function for creating one-way, two-way, and multi-way percentage tables (nothing special there really). Ctab can now print more than one percentage type, as well as table marginals. The first special model in catspec is

I've uploaded a new version of "catspec" to CRAN. Catspec is for estimating certain "special categorical" models. It also contains "ctab", a function for creating one-way, two-way, and multi-way percentage tables (nothing special there really). Ctab can now print more than one percentage type, as well as table marginals. The first special model in catspec is

Hi R users, Is is possible for me to use the try function with boot? I would to do the bootstraping with a nonlinear model(it works well when R < 1000). But it does not work very well (when R is large) thus I try to use "try" to resolve. I put the try function in two cases: case1: put the try in front of the boot > c1.try<-try(boot(c1data, statistic = c1.fun,

------------------------------------------------------------------------ ------------------------------------------------------------------------ New versions 2.3 of our distr-family of packages are now available on CRAN. (i.e.; startupmsg, SweaveListingUtils, distr, distrEx, distrDoc, distrEllipse, distrMod, distrSim, distrTEst, distrTeach) Most importantly, we have included: +

------------------------------------------------------------------------ ------------------------------------------------------------------------ New versions 2.3 of our distr-family of packages are now available on CRAN. (i.e.; startupmsg, SweaveListingUtils, distr, distrEx, distrDoc, distrEllipse, distrMod, distrSim, distrTEst, distrTeach) Most importantly, we have included: +

I am reading the Mining of Massive Datasets Book by Rajaraman and Ullman. It has a good explanation of Recommendation System at Chapter 9. But what are the relationship between 1) SVD (Singular Decomposition) 2) UV-Decomposition 3) NMF (Non-negative Matrix Factorization) In particular, it seems 2) and 3) can be very similar. Is it right? Thanks. -- View this message in context:

Hi, I want to implement a '[' for an S4 class, that behaves differently when called with a single index argument or multiple indexes (possibly missing), like what happens when subsetting matrices x[i] vs. x[i, ]. I manage to do it using nargs() and checking if drop is missing (see code below), but when I want to add an extra argument to the method (before drop), then the parent call

Dear Tony, thanks for the tip with "nargs", when suitably applied, this answers the problem. The behaviour of "nargs" in S4 methods has some subtleties compared to that in normal functions, as shown in the example below. I admit that this is what had earlier created some confusion about the semantics of "nargs". From the perspective of "nargs" and its

Hello, JIT compiler interferes with internal R completions: compiler::enableJIT(2) utils:::functionArgs("density", '') gives: utils:::functionArgs("density", '') Note: no visible global function definition for 'bw.nrd0' Note: no visible global function definition for 'bw.nrd' Note: no visible global function definition for 'bw.ucv'

Hello, I would like to plot specific SNPs with their exact locations on a chromosome. Based on my genotyping results I would like to separate these SNPs in three different categories: 1, 2 and 3 and use different colours to represent these categories. The script below generates the sample data. I can plot these with the image function using the following: val <- 1:3 samp <- sample(val,

----------------------------------------------------------------------------------------- Packages for the computation of optimally robust estimators ----------------------------------------------------------------------------------------- We would like to announce the availability on CRAN (with possibly a minor delay until on every mirror) of new versions of our packages for the computation of

----------------------------------------------------------------------------------------- Packages for the computation of optimally robust estimators ----------------------------------------------------------------------------------------- We would like to announce the availability on CRAN (with possibly a minor delay until on every mirror) of new versions of our packages for the computation of

I initially sent this to the biocore mailing list - but it was suggested that r-devel would also find it interesting. Many of us use a macro like #define CALL_DEF(fname, nargs) { #fname, (DL_FUNC)&fname, nargs} for use in function registration for use with .Call. For example, using the example from R Extension manual, if we want to register a C function myCall with three arguments, we

Applying the following patches closes the following task (part 1 was already taken care of). TASK: New Problems STATUS: Open FROM: <Kurt.Hornik@ci.tuwien.ac.at> New minor remarks: * The documentation for `image' still has the old order z, x, y. * Perhaps one should add `par(ask = T)' in the image demo? * Perhaps one should save the original value

In R's sprintf() if any of the arguments has length 0 the function aborts. E.g., > sprintf("%d", integer(0)) Error in sprintf("%d", integer(0)) : zero-length argument > sprintf(character(), integer(0)) Error in sprintf(character(), integer(0)) : 'fmt' is not a non-empty character vector This comes up in code like x[nchar(x)==0] <-