Multiple-key merges arise when more than one variable is required to uniquely identify the observations in your data. In Merging data, part 1, I discussed single-key merges such as
. merge 1:1 personid using ...
In that discussion, each observation in the dataset could be uniquely identified on the basis of a single variable. In panel or longitudinal datasets, there are multiple observations on each person or thing and to uniquely identify the observations, we need at least two key variables, such as Read more…
Between now and the end of the year, the annual Stata Conference in the United States will take place along with five other Stata meetings in countries around the world.
Stata conferences and meetings feature talks by both Stata users and Stata developers and provide an opportunity to help shape the future of Stata development by interacting with and providing feedback directly to StataCorp personnel.
The talks range from longer presentations by invited speakers to shorter talks demonstrating the use of Stata in a variety of fields. Some talks are statistical in nature while others focus on data management, graphics, or programming in Stata. New enhancements to Stata created both by users and by StataCorp are often featured in talks.
The full schedule of upcoming meetings is Read more…
Merging concerns combining datasets on the same observations to produce a result with more variables. We will call the datasets one.dta and two.dta.
When it comes to combining datasets, the alternative to merging is appending, which is combining datasets on the same variables to produce a result with more observations. Appending datasets is not the subject for today. But just to fix ideas, appending looks like this: Read more…
When most people first think about software designed to run on multiple cores such as Stata/MP, they think to themselves, two cores, twice as fast; four cores, four times as fast. They appreciate that reality will somehow intrude so that two cores won’t really be twice as fast as one, but they imagine the intrusion is something like friction and nothing that an intelligently placed drop of oil can’t improve.
In fact, something inherent intrudes. In any process to accomplish something—even physical processes—some parts may be able to to be performed in parallel, but there are invariably parts that just have to be performed one after the other. Anyone who cooks knows that you sometimes add some ingredients, cook a bit, and then add others, and cook some more. So it is, too, with calculating xt = f(xt-1) for t=1 to 100 and t0=1. Depending on the form of f(), sometimes there’s no alternative to calculating x1 = f(x0), then calculating x2 = f(x1), and so on. Read more…
Jim Hufford, Esq. had his first Stata lesson: “This is going to be awesome when I understand what all those little letters and things mean.”
Along those lines—awesome—Jim may want to see these nice Stata scatterplots from the “wannabe economists of the Graduate Institute of International and Development Studies in Geneva” at Rigotnomics.
If you want to graph data onto maps using Stata—and see another awesome graph—see Mitch Abdon’s “Fun with maps in Stata” over at the Stata Daily.
This link was passed on to me by my friend Marcello. I’ve been bold enough to make up words such as eigenaxis and eigenpoint, but it takes real courage to suggest redefining π, even when you’re right!
After seeing the video, you can go here and here to learn more about what is being proposed.
Don’t click on comments until you’ve seen the video. Ms. Hart does a better job presenting the proposal than any of us can.
Last time, I showed you a way to graph and to think about matrices. This time, I want to apply the technique to eigenvalues and eigenvectors. The point is to give you a picture that will guide your intuition, just as it was previously.
Before I go on, several people asked after reading part 1 for the code I used to generate the graphs. Here it is, both for part 1 and part 2: matrixcode.zip. Read more…
To get to them, just click on the title of the post and scroll to the bottom of the page. To begin, we are allowing guest comments, so you do not even have to register, although registration is easy.
I want to show you a way of picturing and thinking about matrices. The topic for today is the square matrix, which we will call A. I’m going to show you a way of graphing square matrices, although we will have to limit ourselves to the 2 x 2 case. That will be, as they say, without loss of generality. The technique I’m about to show you could be used with 3 x 3 matrices if you had a better 3-dimensional monitor, and as will be revealed, it could be used on 3 x 2 and 2 x 3 matrices, too. If you had more imagination, we could use the technique on 4 x 4, 5 x 5, and even higher-dimensional matrices. Read more…
Our target date for tuning on comments is Wednesday of next week. Don’t hold us to it, but we’re optimistic on meeting our deadline.
In the meantime, Bill Gould is so excited he’s put on hold his latest blog entry. It’s about linear algebra—matrices in particular—so it won’t exactly go out of date, and he’s looking forward to seeing the comments. Bill’s very proud of what he’s written, so be gentle. We’ll put up his posting right after comments are enabled.