agentq

I researched & prototyped (in R), and ultimately put into production (C++) a core set of spectral risk analysis analytics that replaced outdated VaR and vol forecasts for an extremely large asset management firm and left immediately afterwards. Technically speaking, guided risk mgmt/investment decisions at the trillion-dollar scale, ran as-is for 8-10 years before being recently re-implemented in some other language.

80s.nyc has a somewhat similar street view using archival images from the 80s

Monte Carlo simulation is the most oft-cited example. This tends to be most relevant to quickly American pricing options, or anything that isn't easily done in closed-form.

-- closed 2011 Nov 28.

For anyone who doesn't want to roll their own FFT, take a look at this excellent pure C implementation: http://www.fftw.org/

I actually find base R excellent for data munging and manipulation, even without using additional packages. Here is a reproducible example that very easily accomplishes what you were trying to do (first two lines just set up a sample data frame)

  set.seed(123)
  dfrm <- data.frame(height=runif(20),
                     name=paste(sample(LETTERS[1:5],20,replace=TRUE),letters[1:20]))
  subset(dfrm, grepl('^D',name), sel=height)

Basic R functions like subset, transform, with(in), reshape, aggregate, (a,ma,ta,sa,va}pply, match, grep(l), by, split, table, etc. allow you to accomplish just about any data frame munging you might want. Add on the plyr, reshape2, data.table, xts/zoo packages and you're ready to tackle just about anything.

I'm not a big fan of sqldf because imo R is not supposed to act like SQL. Using sqldf in practice would require a lot of query string manipulation and takes away from the nice functional features of R.

Nevertheless, it is very easy to write incomprehensible R code. The best way to avoid this is to take one of the existing style guides (Google, Hadley Wickham's) and adopt it seriously.

I tried to convince the croupier that zero was an even number, but alas ...

this is pretty neat! one quick thing -- 40th and 8th ave -> grand central: suggests S grand central -> 53rd and park: suggests 6 40th and 8th -> 53rd and park: some crazy sequence of bus routes.

http://sandytransit.alastair.is/opentripplanner-webapp/index... Nov 01 2012 21:26:37 GMT-0400 (Eastern Daylight Time)&arriveBy=false&itinID=1&wheelchair=false&preferredRoutes=&unpreferredRoutes=

no love for J?

they don't mention NSPR. is it dead? http://www.mozilla.org/projects/nspr/

In financial practice, asset-level PCA isn't as common, especially in systems where covariance estimation is fraught with misspecification errors. Instead, individual securities first condensed to factors (e.g., for equity some examples are book/price, momentum, large vs. small cap, etc.).

http://www.jwz.org/dadadodo/ DadaDodo is a fairly old implementation that may be of interest.

"He’s not alone in paying for the cache of being among the first to purchase apple products."

cache? sigh

The first thing I'd recommend doing is find the unique entries THEN sort. Unless uniq has vastly better performance on sorted files...

To further goad the OP to immediately leave his current job: between junior and senior year of college, I made a bit more than the OP's yearly pay in a 12wk internship.

Please, for your wife and kid(s), get out of this horrible situation.

Thanks, I'll check it out!

My programming background is fairly extensive in non-functional languages. I work in finance, and the company I joined uses R for a considerable amount of model prototyping.

I'd really like to switch to Python+numpy/scipy, but I haven't been able to find an equivalent of a data.frame, or some numeric+string data structure that allows for easy slicing on both.

Does anybody have any suggestions?

s/ia/a/

I am a quantitative analyst at a large asset management firm -- I focus on risk models and alpha-generating strategies. Though we have separate developer teams, my job requires considerable hacking.

LMDDGTFY:

http://lmddgtfy.com/?q=goog-411+phoneme&v=

and:

http://www.newsley.com

Understood. The specific aspect of Digg that I am comparing recent trends to is that of submission of duplicate articles, and the inevitable notification thereof by other users.

A small example: http://www.google.com/search?hl=en&q=site:http://news.yc...

HN is starting to feel like Digg. http://news.ycombinator.com/item?id=1160552

Even better, just hit Shift+I ...

Glad you like it!

Splitting in Smooth Gestures means taking the current tab and those to the right and moving them to a separate window. Merging takes the current window's tabs and appends them to the last focused window.

I'd also suggest "Smooth Gestures"

https://chrome.google.com/extensions/detail/lfkgmnnajiljnolc...

Some of the functionality is pretty cool (i.e., haven't seen it in All-in-One Gestures for Firefox), like merging and splitting tabs.

What will end up happening to the 'real bad guys' http://xkcd.com/538/

It's good to see that the public's relative need for weather(.com) forecasts has not changed in the last twelve years.

In the particular case of integer ids, however, can't you just make sure what's being passed is an integer? Similarly, for a 'simple' username, check against "^[a-zA-Z0-9]+$"?

If anyone is interested in a more academic (i.e., behavioral economics / information theory-based) discussion of "spin" or "slanting," I'd recommend this paper by Mullainathan and Shleifer:

The Market for News

http://www.economics.harvard.edu/faculty/shleifer/files/mark...