similar to: How to suppress 'Loading required package ...' via Depends/Imports

R CMD check really hates it when my .onLoad() function contains suppressMessages(library(foo)) However, _and for non-public packages not going to CRAN_ I prefer doing this over using explicit Depends or import statements in the NAMESPACE file as the latter do not give me an ability to make the loading less verbose. With the R universe of packages being as vast as at is, a simple (non-public)

Hi When I run my script using ggplot and geom_smooth I get messages that I would like to suppress: p <- ggplot(dataSubset) p <- p + aes(x = as.Date(factor(key),format="%Y%m%d")) + geom_line() p <- p + geom_smooth(span=0.2,se=FALSE,size=0.7) The messages look like this: geom_smooth: method="auto" and size of largest group is <1000, so using loess. Use 'method

The suppressMessages and suppressWarnings functions currently suppress all the message or warnings that are generated by the input expression. The ability to suppress only specific messages or warnings is sometimes useful, particularly for cases like file import where there are lots of things that can go wrong. Suppressing only messages that match a regular expression has rightly been rejected

I just upgraded to Ubuntu 8.10 (i386) from 8.04. After the upgrade, I ran update.packages(.libPaths()[1]) in R to get the packages installed from source up to date too. Unfortunately, two packages could not be updated: mclust and mboost. In both cases, the error I got mentioned lf77blas. Here's the output for mboost: * Installing *source* package 'mboost' ... ** libs gcc -std=gnu99

Hi UseRs - I am new to R, and could use some help making out-of-sample predictions using a boosting model (the mboost command). The issue is complicated by the fact that I have panel data (time by country), and am estimating the model separately for each country. FYI, this is monthly data and I have 1986m1 - 2009m12 for 9 countries. To give you a flavor of what I am doing, here is a simple

I'm using the function gee from the library(gee) gee(Y~X,id=clust.id,corstr="exchangeable",b=tmc$coef,family=binomial(link=logit),silent=T) Every time it runs, it dutifully prints out Beginning Cgee S-function, @(#) geeformula.q 4.13 98/01/27 user's initial regression estimate [,1] [1,] -4.5278335 [2,] -0.2737999 [3,] -0.9528306 [4,] 0.9393861 [5,]

Hi, I use a mboost model to predict my dependent variable on new data. I get the following warning message: In bs(mf[[i]], knots = args$knots[[i]]$knots, degree = args$degree, : some 'x' values beyond boundary knots may cause ill-conditioned bases The new predicted values are partly negative although the variable in the training data ranges from 3 to 8 on a numeric scale. In order to

I'm running R 2.10.1 with mboost 2.0 in order to build predictive models . I am performing prediction on a binomial outcome, using a linear function (glmboost). However, I am running into some confusion regarding centering. (I am not aware of an mboost-specific mailing list, so if the main R list is not the right place for this topic, please let me know.) The boost_control() function allows

I would like to simulate the effect of the command-line option --quiet from user-level scripts and startup code. From src/main/CommandLineArgs.c I learn that Rp->R_Quiet is set, and I see how that is used in main/main.c. I would use this from code in Rprofile.site. In other words, I want to be silent when --quiet is used (as e.g. by littler or Rscript) but not by R itself in normal

Awesome, this gets the job done. To answer your question: When using C or C++ via Rinside or within a package, those functions do not listen to suppressMessages, e.g. `Rprintf` keeps printing to the console. Since it's common to use wrapper functions in R anyway, they can run `are_messages_suppressed` and pass the information on to an explicit `verbose` argument of the C / C++ function.

Dear Russ, I had the same problem in my vignettes and setting both message and warning to FALSE seems to remove all unwanted output: ```{r message=FALSE, warning=FALSE} library("afex") library("ggplot2") library("cowplot") theme_set(theme_grey()) ``` Result: https://cran.r-project.org/web/packages/afex/vignettes/afex_plot_introduction.html Best, Henrik Am Di.,

Hi all, I would like to create a function that detects if suppressMessages has been invoked upon running that same function. I was looking through {https://cran.r-project.org/doc/manuals/r-release/R-ints.html}, but I haven't found an answer. I do not understand **how** suppressMessages works. I have not received an answer on SO

Dear list, I'm trying to suppress/redirect/squash the output from commands like install.packages, or download.file. The problem is that none of: sink(..., type="message"), sink(..., type="output"), capture.output, suppressMessages are quite doing the trick. Output gets written to the stderr stream, despite any combination of the above suppression commands. According to

I'm getting started in R, and I'm trying to use one of the gradient boosting packages, mboost. I'm already installed the package with install.packages("mboost") and loaded it with library(mboost). My problem is that when I attempt to call glmboost, I get a message that " Error in glmboost() : no applicable method for "glmboost" ". Does anybody have

I'm attempting to fit boosted regression trees to a censored response using IPCW weighting. I've implemented this through two libraries, mboost and gbm, which I believe should yield models that would perform comparably. This, however, is not the case - mboost performs much better. This seems odd. This issue is meaningful since the output of this regression needs to be implemented in a

Hi all, First of all, I'm a novice R user (less that a week), so perhaps my code isn't very efficient. Using the MBoost package I created a model using the following command and saved it to a file for later use: model <- gamboost(fpfm,data=SampleClusterData,baselearner="bbs") # Creating a model save(model,file="model.RData") # Saving a model After this, during a

Dear all, I am puzzled by R's memory usage when calling the blackboost function from package mboost to estimate a Gradient boosting model on a simulated dataset with 20 correlated variables and 100,000 obs. The blackboost object created by the function is only 15.3Mb, but R's memory usage increases by about 3.9Gb during the estimation of the model and the memory is not released even after

Bill, Is your conclusion to just update the code and enforce using the most recent version of R? Dayne On Wed, Jul 15, 2015 at 4:44 PM, Dayne Filer <dayne.filer at gmail.com> wrote: > David, > > If you are referring to the solution that would be: > > rapply(list(test), eval, envir = fenv) > > I thought I explained in the question that the above code does not work.

Another aspect of the change is (using TERR's RinR package): > options(REvaluators=list(makeREvaluator("R-3.1.3"), makeREvaluator("R-3.2.0"))) > RCompare(rapply(list(quote(function(x)x),list(quote(pi),quote(7-4))), function(arg)typeof(arg))) R version 3.1.3 (2015-03-09) R version 3.2.0 (2015-04-16) [1,] [1]

Full_Name: Ivan the Terrible Version: 2.9.2 OS: Windows XP SP3 Submission from: (NULL) (89.110.13.151) When using the method blackboost_fit of the package mboost appear following error : Error in party:::get_variables(obj at responses) : trying to get slot "responses" from an object (class "boost_data") that is not an S4 object Simple test case that produce bug: