crowding

Sorry, but yes. In my state, crosswalks are legally defined to exist at every street corner whether or not they are painted lines. Furthermore, the obligation of drivers to yield to pedestrians in crosswalks starts when they step into the street and not a moment before. (Standing on the sidewalk means nothing even if there is a painted crosswalk). Stepping out into a safe gap in the curbside lane and expecting traffic to stop is legally prescribed behavior and is the behavior drivers should expect. And pedestrians should encourage drivers to expect that behavior by actually behaving that way.

Seattle? Place yourself in the bike lane stopped at Eastlake and Fuhrman southbound. Very common commute route. No way to not be in the bike lane there given you just crossed the U bridge. (Unless you like riding on steel grating while drivers honk at you.) Then try to make the left onto Harvard Ave (again, extremely popular route) after the light turns green. You have one block to move left across two lanes. Post youtube if possible. I guarantee that proceeding across Fuhrman against the red light, doing your lane changes in the absence of traffic, is safer and less antagonizing if there is even moderate traffic. Only other safe alternative is to use the pedestrian crossings, which kind of fucking proves the point here. There's a million little situations like this.

A baseline rate of wildcards among cyclists encourages greater attentiveness in drivers that interact with me, whether or not I am a wildcard in that moment. It's a herd immunity sort of thing. The practices called "defensive driving" would not be followed by anyone unless there were something to defend against.

In WA where I am, and I believe in CA, standing on the curb facing the crosswalk != using a crosswalk. Standing around looking like you might use the crosswalk someday doesn't mean anything; using the crosswalk (and having right of way) starts only from the moment they step off the sidewalk. The WA code makes this pretty clear; CA uses the specific phrase "withinin a crosswalk" which makes me believe the interpretation is the same there.

So waving through someone who's not actively crossing is not correctly yielding the right of way. OTOH, drivers should bloody well expect pedestrians to start crossing in front of them when you haven't stopped yet (both states say that a pedestrian may not step out if there is inadequate room for the car to react and stop; by the contrapositive a pedestrian may step out in front of a car if there is adequate distance.)

Matlab is not a JVM language, it just has some ability to call Java built in, and some of the IDE is in Java implementation. Launch Matlab without booting a JVM: matlab -nojvm

In MATTEL, the crossbar of the E is placed in the exact center.

Latest James Hague and/or Michael O. Church blog.

Split keyboard! There are two space bars.

They're both designed around completely in-memory arrays, which are passed around by-value with a copy-on-write scheme.

For R there is the bigmem package for mmapped arrays. And the "compiler" JIT packace is included since R 2.13.

I've seen that link before. See above re: one group's willingness to talk about the shortcomings versus another organization's preference to paper over it with marketing.

Gelman and Hill is a nice book organized specifically around regression.

you know, just two weeks ago I mapped my spacebar to be both space and Meta.

Somewhat fittingly, though.

I've used Matlab for about 15 years and R for about 3. Matlab burned me pretty badly during my graduate career; two weeks after deciding to learn R, I'd recreated a data analysis/modeling/graphing problem I'd previously done in MATLAB, using about one third the amount of code in R. Perhaps R and its available libraries better suit the way I think about problems, but most people in my department agree I code circles around them in Matlab, and I've since repeated the experiment with similar results.

So, some reasons a Matlab user might want to consider learning R:

-- R is currently the lingua franca for academic statisticians. New methods papers, textbooks, and toolkits are much more likely to ship with R libraries and implementations then Matlab or anything else.

-- Speaking of statistics, the MathWorks' most recent revamping of the Statistics Toolbox is an obvious imitation and pale shadow of base R, giving you a more verbose way to do half of what base R does for statistics, and then R has everthing available on CRAN to add to that.

-- R is a smaller, yet more expressive language. To be fair, it has about the same density of WTF and non-orthogonality as Matlab (which see, Patrick Burns' "The R Inferno") but makes up for it by being much better at functional programming, and by having more of the Lisp nature in general (R is homoiconic; you can write R code that manipulates R code). If you want object-oriented programming you're about equally screwed in both languages though. R has syntactic support for named/optional arguments to functions, as opposed to Matlab's horrible InputParser/nargin hacks.

-- and in general the idea of giving names to things (rows and columns of a matrix, individual elements, function arguments) is pervasively supported in R. Matlab doesn't even have a decent approximation of a hashtable.

-- R is not quite as insistent on being its own universe. For example, you can write R scripts invokable directly from the shell, without jumping through awful "expect" style hoops and waiting 30 seconds for system startup / license server failure every invocation. For reproducible analysis you really want a build tool ( http://archive.nodalpoint.org/2007/03/18/a_pipeline_is_a_mak... ); so having your analysis scripts being callable by Make or SCons is a no-brainer.

-- Speaking of reproducibility, much of the "reproducible research" movement (which basically says, "hey, maybe scientific data analyses and papers should be done with version control, build automation, and maybe even testing, like software people have been doing since forever") is centered around R. I'm currently doing a project with "knitr," an R library that helps writing reproducible reports; if I want to talk about a particular graph or cite a p-value, I don't manually copypasta the data into a word processor; I write in my document the command to compute the value or plot the graph, and it gets updated whenever I render to a PDF. That ensures that results keep track of any changes in dataset or analysis.

-- The R community in general is more frank about its shortcomings and limitations, which might only be possible in a free software project. For both systems, you can say, word for word, that "there are a lot of awful decisions that (R/MATLAB) inherited due to (S/MATLAB)'s 1970s origins in (John Chambers/Cleve Moler)'s attempt to build a useful sort of interactive shell over Fortran numerics libraries, which it turns out should not be what you build a real programming language on top of." The difference is that the R folks will talk openly about the ways in which R sucks, but you won't get any such acknowledgement from the Mathworks.

-- R-help is both more active and contains smarter inhabitants than comp.soft-sys.matlab. Similarly for R/Matlab questions on StackOverflow.

-- R has a much better packaging system. Actually I should change the emphasis: R even has a packaging system. Libraries install from CRAN/Bioconductor/Rforce with one command, and installing them doesn't tromp all over the global namespace. The code is much higher quality than you find on the Mathworks File Exchange; most of the time I look on the File Exchange anything that looks like it solves my immediate problem hasn't been updated for 5 years and no longer works. CRAN on the other hand has maintainers who will remove packages that stop working. Consequently, people take more ownership of their packages.

-- ggplot2 is the best library in any language for taking your data and making a useful 2d plot out of it. I've written hundreds of lines of Matlab to build graphics that are a couple of phrases in ggplot. On the other hand, Matlab is better at 3d graphing (which I hardly use) and interactive graphics (but there's a lot of people attacking that on the R side.)

-- Simlarly I've written hundreds of lines of Matlab to do data manipulation operations that are like breathing air with Hadley's other great library, plyr.

-- Downsides? R is somewhat slower (if you want to compare two laughably slow languages; we're talking roughly CPython vs Ruby). Matlab has a better IDE with better debugging facilities. Depending on your field you might have more colleagues that are familiar with Matlab (true for engineering, definitely false for statistics.) R's online help is harder to navigate, which lends it a somewhat more difficult learning curve. Actually creating a package to distribute your code is pretty hard to figure out.

I can see that from this distance -- I should have been more specific about is being a downside of the way MATLAB is only half-assedly array-oriented, not necessarily a feature of all array oriented languages.

The idea appears to be that array languages have builtin functions for operations that would require map/reduce/etc in the applicative programming paradigm. I agree that is convenient, but the downside is that only array operations that are supported this way are the ones that are anticipated by the language designer. If you want to split up an array in some way other than intended, you're back to applicative programming, so your language needs good support for that too.

I would argue that the more important thing that makes something an "array language" is that scatter/gather operations on arrays have syntactic support, as described here:

http://prog21.dadgum.com/141.html

As a personal anecdote: In my thesis work I switched most of my data analysis workflow from MATLAB to R. In terms of paradigms I'd say R is a slightly worse array-language (although it does have builtin syntax for things that require messing with sub2ind() in MATLAB) but a much better functional language than MATLAB. The empirical result is that I finished my first analysis project -- including the time it took to learn R -- faster than it had taken me to do a similar task in MATLAB, using 1/3 the code. Add to that that there is presently more active development of open graphics and statistical analysis libraries in R, and I haven't really looked back, though I occasionally think of picking up an APL-derivative like J to play with.

It also allows the file to be widely disseminated and mirrored before revealing what it contains, as an anti-DDOS measure.