[caption id=“attachment_825” align=“alignleft” width=“250” caption=“André-Louis Cholesky is my homeboy”][/caption] When I did a brief post three days ago I had no plans on writing two more posts on correlated random number generation. But I’ve gotten a couple of emails, a few comments, and some Twitter feedback. In response to my first post, Gappy, calls me out and says, “the way mensches do multivariate (log)normal variates is via Cholesky. It’s simple, instructive, and fast.
So after yesterday’s post on Simple Simulation using Copulas I got a very nice email that basically begged the question, “Dude, why are you making this so hard?” The author pointed out that if what I really want is a Gaussian correlation structure for Gaussian distributions then I could simply use the mvrnorm() function from the MASS package. Well I did a quick ?mvrnorm and, I’ll be damned, he’s right! The advantage of using a copula is the ability to simulate correlation structures where the correlation is different for different levels of values.
A friend of mine gave me a call last week and was wondering if I had a little R code that could illustrate how to do a Cholesky decomposition. He ultimately wanted to build a Monte Carlo model with correlated variables. I pointed him to a number of packages that do Cholesky decomp but then I recommended he consider just using a Gaussian Copula and R for the whole simulation.
[caption id=“attachment_775” align=“alignleft” width=“250” caption=“Radiant Heat System. Not in my house… yet! “][/caption] My wife and I bought a foreclosed house a few months ago. This house had been part of mortgage fraud and we bought it at auction. Interesting life experience, to say the least. The finished basement was built with radiant heat tubing poured into the concrete. These pipes are designed to be hooked to a hot water heater so the warm water can provide radiant heat through the floors in the basement.
I do some work from home, some work from an office in Chicago and some work on the road. It’s not uncommon for me to want to tunnel all my web traffic through a VPN tunnel. In one of my previous blog posts I alluded to using Amazon EC2 as a way to get around your corporate IT mind control voyeurs service providers. This tunneling method is one of the 5 or so ways I have used EC2 to set up a tunnel.
I’ve been continuing to muck around with using R inside of Amazon Elastic Map reduce jobs. I’ve been working on abstracting the lapply() logic so that R will farm the pieces out to Amazon EMR. This is coming along really well, thanks in no small part to the Stack Overflow [r] community. I have no idea how crappy coders like me got anything at all done before the Interwebs. One of the immediate hurdles faced when trying to use AMZN EMR in anger is that the default version of R on EMR is 2.
I’m kinda blown away by the number of folks who have joined the Chicago R User Group (RUG) in the last few weeks. As of this morning we have 65 people signed up for the group and 25 who have said that they are planning on attending the meetup this Thursday (yes, only 3 days away!) I’m very pleased that this many people in Chicago find the R language interesting and/or valuable.
On Tuesday May 4th at 9:30 PM central, 10:30 eastern, I’ll be giving a live online presentation as part of the Vconf.org open conference series. I’ll be speaking about R and why I started using R a couple years ago. This is NOT going to be a technical presentation but rather an illustration of how an R convert was created and why R became part of my daily tool set.
Back in November 2009 Wired wrote an article about some grad students who decided to try to stochastically model throwing darts. Because I don’t actually read printed material I didn’t see the article until a couple of months ago. My immediate thought was, “hey, I drink beer. I throw darts. I build stochastic models. Why haven’t I done this?” Well we all know why I haven’t done this. I have a job and a 2 year old daughter and I like my wife.
[caption id=“attachment_705” align=“alignleft” width=“283” caption=““as we know, there are known knowns; there are things we know we know. We also know there are known unknowns; that is to say we know there are some things we do not know. But there are also unknown unknowns – the ones we don’t know we don’t know.” US Defense Secretary Donald Rumsfeld, February 12, 2002”][/caption] I’ve been a long time reader of the blog “Messy Matters” (which invokes terrible images now that I am potty training a toddler).