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### Blog - Burns Statistics

burns-stat.comerror This was not in the list above because its default value is NULL. That is the wrong value for almost all people almost all of the time. There are (at least) two better values. The first better value is dump.frames: R> options(error=dump.frames) R> stop("here is an error") Error: here is an error R> debugger() Message: Error: here is an error Available environments had calls: 1: stop("here is an error") Enter an environment number, or 0 to exit Selection: The second better value is recover: R> options(error=recover) R> stop("here is a second errrrror") Error: here is a second errrrror No suitable frames for recover() The (important) difference is that with recover you are thrown into the debugger automatically (if possible) when you encounter an error. In contrast you need to call debugger yourself if you use dump.frames.Blog - Burns Statistics -

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debugger() Message: Error: here is an error Available environments had calls: 1: stop("here is an error") Enter an environment number, or 0 to exit Selection: The second better value is recover: R> options(error=recover) R> stop("here is a second errrrror") Error: here is a second errrrror No suitable frames for recover() The (important) difference is that with recover you are thrown into the debugger automatically (if possible) when you encounter an error. In contrast you need to call debugger yourself if you use dump.frames.
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That was 7 years ago. There were on the order of 600 packages on CRAN. Present Things are different now. As of St. Paddy?s Day there were 4399 packages on CRAN. If other major repositories are included, then the number of packages exceeds 6000. It is unimaginable for something similar to happen in academia now. In particular, the UCLA site no longer has the technical report available ? instead there are substantial resources about R. In academia, R is highly accepted, and ? in some fields ? very dominant. In commercial companies R is in a similar position now to how it was in academia in 2006. Future Which leads to my prediction: In the year 2020 R will be a dominant force in commerce similar to how it currently dominates in academia. I?m not thinking the transition is automatic. In academia R?s competition was SAS, SPSS, Stata, Minitab and some others. In commerce R?s competition is primarily Excel.Blog - Burns Statistics -

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I edited material from the thread, got some additional views privately, and added a few flourishes myself to produce: R Relative to Statistical Packages (pdf).Blog - Burns Statistics -

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a technical report put out by the statistical computing group at UCLA. The report in question talked mainly about SAS, SPSS and Stata. It talked briefly ? and not especially positively ? about R.Blog - Burns Statistics -

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Online Math Degrees has a page of ?100 savvy sites on statistics and quantitative analysis?Blog - Burns Statistics -

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CRAN is the biggest with over 4000 packages. Bioconductor focuses on genomics data and has over 600 packages. Omegahat is mainly about connecting R to other languages.Blog - Burns Statistics -

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Stackoverflow and the various mailing lists are better equipped to handle technical questions. The groups can be used for the types of questions that are on Quora, but I think there is more potential power in the groups than just that.Blog - Burns Statistics -

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LinkedIn has a number of groups devoted to R. Some of them are: The R Project for Statistical Computing R Programming R/Finance R Users subgroup of Statistics and Analytics Consultants R Professionals Network My view of these groups is that they are an excellent answer to an unknown question. I?m sure that they can be quite valuable, but I?m not sure for what.Blog - Burns Statistics -

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Quora is a place to ask open-ended questions and questions of opinion. It includes questions aboutBlog - Burns Statistics -

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https://twitter.com/#rstatsBlog - Burns Statistics -

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There are many blogs that talk about R. You can scour the web for them (there are lots), or you can go to R-bloggers where they are aggregated. (If you know of a blog that has posts about R but is not on R-bloggers, then please encourage them to join.) Another aggregator is statsblogs. As the name suggests it is focused on statistics, but it includes blogs about R.Blog - Burns Statistics -

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Many prefer to look at R-help via a mechanism other than email ? gmane for instance.Blog - Burns Statistics -

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If your question is more statistical than computational, then Cross Validated will be a good place to ask it.Blog - Burns Statistics -

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Stackoverflow seems to have become the most popular venue to ask for help with R. There is an R tag which, by the way, you can subscribe to with RSS. Warning: Don?t ask questions on Stackoverflow that require opinion. Stackoverflow is for objective facts. Go elsewhere (see below) if you are seeking opinions.Blog - Burns Statistics -

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What are the three most useful things in Matlab but not in R? For me it is the availability of the two great optimization modeling frameworks CVX and YalMip. And if you are from the field of engineering and need to do simulation tasks for which MatLab/Simulink does provide exactly what you need, then it is the right choice? but if you are doing this kind of stuff then you most likely never considered to switch to R anyways.Blog - Burns Statistics -

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What are use cases of Matlab over R, and vice versa? I?d say that certain (if not most) optimization tasks are still not convincingly implemented in R at all. It is sad to see that people who quit MatLab for an open source alternative are choosing Python over R ? which I do understand, because most optimization packages in R do not make any sense if you look at them from the Mathematical Programming viewpoint. Statisticians certainly do have a different approach to optimization.Blog - Burns Statistics -

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What is your general attitude about R versus Matlab now? I really love R nowadays and personally could not imagine switching back to MatLab anymore ? although out of curiosity I am following the Julia Language project at http://www.julialang.org/ so in case I would ever need to switch back to MatLab, I would do so indirectly via Julia.Blog - Burns Statistics -

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one issue that really helped to speed up the transition was the availability of RStudio, which finally took the nerdy feeling out of RBlog - Burns Statistics -

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