From BWR The above graph is derived from data scraped from TEPCO press releases. Every hour or so for the first few days of the crisis, a TEPCO van would record radiation (probably Beta/Gamma, but the translation is unclear) at … Continue reading →
Blog Archives
No simulation is complete without a gif
I promise this is my last post on the now week and a half old π pay! Building on the last post, I figured I could show how convergence actually works in the estimation algorithm. If you’ll recall, we plotted … Continue reading →
More pi plus 1 (or plus 0.01) day fun
Since I just didn’t get enough this morning, I spent some more time fooling around with estimating pi. Since I was basically counting the number of random x,y pairs inside a quarter circle and computing a sample average for more … Continue reading →
I’m late for π day
It is officially no longer pi day, but I didn’t see this Drew Conway post about estimating pi until just a few minutes ago. Because Google Reader doesn’t show github embeds, I also got to try it without seeing Drew’s … Continue reading →
A Short Return to the Age-Earnings Profile
Two posts ago I mentioned the age-earnings profile but did not provide a regression of log earnings on wage. I also offered, without evidence, that fitting a simple linear regression would be inappropriate. How do I know that? How could … Continue reading →
Our Friend the Age-Earnings Profile
I like Labor Economics. Partially because it has a nice mix of theory and practical empiricism, but mostly because it seems to be a sub-field with a number of agreed upon stylized facts that grow not out of micro theory … Continue reading →
RStudio
All the cool kids are talking about it so I should take some time to plug RStudio, a free open source IDE for R. Unlike some of the “beginner” IDEs like Deducer, RStudio is not designed to offer menu based … Continue reading →
Bootstrapping the Truncated Normal Distribution
Here’s a post generated from my own ignorance of statistics (as opposed to just being marred by it)! In Labor Economics we walked through something called the truncated normal distribution. Truncated distributions come up a lot in the sciences because … Continue reading →
Stationarity
In time series work you often run into difficulties in modeling processes where the overall level of one variable (an input, for example) changes over time but the levels of another variable (an output) do not change. For instance if … Continue reading →
Null Confusion
Talking a bit with my friend Jarrod about math stats and econometrics, we both came to the conclusion that the standard presentation for basic inference is lacking. In an intro or intermediate applied statistics course you learn about first and … Continue reading →
Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).
