similar to: csv version of data in an R object

I've been updating a package and, when installing a local devel version, I get an error "object 'confusionMatrix' not found whilst loading namespace". Looking around online, it appears that this might be related to loading a specific RData file, but it doesn't seem to be the case AFAICT. I've installed the devel version in the last week without issues and the

Hello everyone, I'm stumped. I'd like to create a scatterplot matrix with circular reference lines. Here is an example in 2d: library(ellipse) set.seed(1) dat <- matrix(rnorm(300), ncol = 3) colnames(dat) <- c("X1", "X2", "X3") dat <- as.data.frame(dat) grps <- factor(rep(letters[1:4], 25)) panel.circ <- function(x, y, ...) { circ1

In my own package, I want to use the default S3 method of the generic function lrtest() from the lmtest package. Since I need only one function from lmtest, I tried to use importFrom in my NAMESPACE: importFrom(lmtest, lrtest) However, this fails R CMD check in the examples: Error in UseMethod("lrtest") : no applicable method for 'lrtest' applied to an object of class

On my MacBook Pro (OS 10.6.8), after updating to R version 2.14.0 (2011-10-31) and reinstalling the Hmisc package, I am unable to load the Hmisc library. Hmisc was working *before* I updated R. Any idea what's wrong? Details below. > install.packages("Hmisc", dependencies=TRUE) trying URL 'http://cran.case.edu/bin/macosx/leopard/contrib/2.14/Hmisc_3.9-0.tgz' Content

The help page for ?Extract says: "When extracting, a numerical, logical or character NA index picks an unknown element and so returns NA in the corresponding element of a logical, integer, numeric, complex or character result, and NULL for a list. (It returns 00 for a raw result.] " However, I seem to be getting different behavior when converting NA's to character indices

Hello R Users: I have 3 packages that I authored and they build and check just fine locally. However, when I try to install the local source packages (from the .tar.gz), I get the following message: Error in `+.POSIXt`(as.POSIXct(origin, tz = tz, ...), x) : could not find function "%is.a%" In addition: Warning message: In install.packages(file.choose(), .libPaths()[1], NULL, type =

Everyone, I've got code in my package that uses LogitBoost from the caTools package. caTools does not have a namespace. My package also uses loads RWeka, which has a namespace, and also has a function called LogitBoost. After loading both packages, how can I be specific about running the version from caTools (since caTools:::LogitBoost won't work)? Thanks, Max

I was trying to produced bagged importance estimates of attributes in earth using the caret package with the following commands:   fit2 <- bagEarth(loyalty ~ ., data=model1, B = 10)   bagImpGCV <- varImp(fit2,value="gcv") My bootstrap estimates are produced however the second command "varImp" produces the following error:    Error in UseMethod("varImp") : no

Hi, source(file,echo=T) will not echo the last comment in "file" if it is the last line in the file. For instance, when sourcing a file containing the following lines #comment 1 a<-1 #comment 2 R will echo > #comment 1 > a<-1 What is the solution to have R echo all of the comment lines? Specific context: This problem arises e.g. in the context of help files (.Rd) whose

I've had a lot of requests for additions to the reproducible research task view that fall into a grey area (to me at least). For example, roxygen2 is a tool that broadly enable reproducibility but I see it more as a tool for better programming. I'm about to check in a new version of the task view that includes packrat and checkpoint, as they seem closer to reproducible research, but also

The CRAN policy page (https://cran.r-project.org/web/packages/policies.html) implies that there is a formal procedure for orphaning a package but none is mentioned in the Extensions manual (https://cran.r-project.org/doc/manuals/r-devel/R-exts.html). This page (https://cran.r-project.org/src/contrib/Orphaned/README) implies that one would simply resubmit the package to CRAN with the text

Dear all, i searched for some classification methods and I have no glue if i took the right once. My problem: I have a matrix with 17000 rows and 33 colums (genes and patients). The patients are grouped into 3 diseases. No I want to classify the patients and for sure i want to know which rows are more helpful for the classification than others. I tried SVM and random forest. Do you think this

Hi, I have a problem on my mac when trying in R to produce png images. I am getting this warnings with the ArrayQualityMetrics package: > arrayQualityMetrics(rma_fatBody, outdir="normData", force =T) The report will be written into directory 'normData'. KernSmooth 2.23 loaded Copyright M. P. Wand 1997-2009 (loaded the KernSmooth namespace) libpng warning: Application built

Everyone, I'm working with scatter plots with different colored symbols (via lattice). I'm currently using these colors for points and lines: col1 <- c(rgb(1, 0, 0), rgb(0, 0, 1), rgb(0, 1, 0), rgb(0.55482458, 0.40350876, 0.04166666), rgb(0, 0, 0)) plot(seq(along = col1), pch = 16, col = col1, cex = 1.5) I'm also using these with transparency (alpha

Hi, I am having problems passing arguments to method="gbm" using the train() function. I would like to train gbm using the laplace distribution or the quantile distribution. here is the code I used and the error: gbm.test <- train(x.enet, y.matrix[,7], method="gbm", distribution=list(name="quantile",alpha=0.5), verbose=FALSE,

Hi, I installed package 'lars' earlier tonight and did not get any sort of error message. ### ** building package indices ... ** testing if installed package can be loaded Loaded lars 0.9-8 * DONE (lars) ### However, when I try to load it, I get ### > library(lars, lib.loc = "~/R/x86_64-redhat-linux-gnu-library/2.11") Error : .onLoad failed in loadNamespace() for

Hi: When I call str() on an mlogit object, I seem to get warnings. This code is from an example provided in the mlogit documentation: library(mlogit) data("Train", package="mlogit") tr<-mlogit.data(Train, shape="wide", choice="choice", varying=4:11, sep="", alt.levels=c(1,2), id="id")

Hello All, Have recently started learning Sweave and Knitr. Am now trying to learn odfWeave as well. Things went pretty smoothly with Sweave and Knitr but I'm having some trouble with odfWeave. My understanding was that odfWeave should work in pretty much the same way as Sweave. With odfWeave, you set up an input .odt file in a folder, run that file through the odfWeave function, and then

Hello: I am running the icecast2.3.2 server and ices0.4 with a perl script which provides the filename of the next track to play. I am reencoding in advance using ffmpeg, which has been very reliable. My main stream is mp3, 64kbps / 44.1 kHz (mono) and I have pre-reencoded the tracks to 32kbps / 22.05 kHz (mono), for a lower data rate stream. At this time, I have not figured out how to get a

Dear All, I am far from being a guru about parallel programming. Most of the time, I rely or randomForest for data mining large datasets. I would like to give a try also to the gradient boosted methods in GBM, but I have a need for parallelization. I normally rely on gbm.fit for speed reasons, and I usually call it this way gbm_model <- gbm.fit(trainRF,prices_train, offset = NULL, misc =