Recently I have been running R from my Android phone. There are some apps on the Google Play Store that seem to let you emulate R, or connect to a remote version. Instead of doing that, I have been running R directly off my phone using the terminal. Rocking now Writing, running #rstats scripts from the terminal with Emacs, pulling data from Fred, making chartz, All from my oh so very smart phone https://t.
In a blog post the dual y-axis chart just say no Tim Duy asks analysts to give up dual y-axis charts for a new year’s resolution. Like with many resolutions, I predict most will fail at this challenge. I also predict few will take it up. Dual y-axis charts are super popular, especially in finance/economics. As you all know, I care a lot about data visualization. And I have been fighting a losing battle against dual y-axis charts for about a decade.
I shared a chart recently on Twitter that got some attention: static version pic.twitter.com/vtD54nXGio — 📈 𝙻𝚎𝚗 𝙺𝚒𝚎𝚏𝚎𝚛 📊 (@lenkiefer) November 14, 2019 But not just any attention (though I do appreciate all your likes and retweets). This was special. Robert Allison [at]RobertAllison__ at SAS replicated the chart with SAS software and wrote a blog about it. These mortgage rates look shady to me. I worked on a lot of SAS stuff early in my days working at Freddie Mac, and Robert’s SAS graph examples were a resource I often used.
This could have been a tweet. Sometimes it is a tweet. After I have taken a break from social media, blogging, etc and I try to get back in the swing I find it incredibly difficult to get restarted. I feel enormous pressure to say something insightful, something funny, something grand. An effective strategy is not to shoot for the stars. Rather than writing something great, I set my sights lower.
Mortgage interest rates have moved about a percentage point lower from where they were a year ago. The housing market seems to have responded favorably. On my way into D.C. the other day to do some business, I joined a Twitter exchange originally between [at]Graykimbrough and Adam Ozimek, [at]ModeledBehavior about the effects of Federal Reserve interest policy on the housing market. Seems unlikely housing market was slowed by trade war.
This post is for me and future me, though if you get something out of that, that’s great too. Here I will jot down some notes on something I’ve been thinking about. Because reasons, I have been interested in Vector Error Correction Models (VECM). I’ve been thinking of the case where you estimate an error correction model, and have available external forecasts for one of the variables. How can you easily construct the conditional forecasts for the VECM in R?
Today I tweeted something that turned out to be pretty popular: US consumer prices pic.twitter.com/LxIxvEnGFe — 📈 𝙻𝚎𝚗 𝙺𝚒𝚎𝚏𝚎𝚛 📊 (@lenkiefer) October 10, 2019 This was an update to a visualization we have talked about here. In this post I want to provide some updated R code to make this visualization taking advantage of the new gganimate api. I’ll also share some code for mortgage rate plots. The code for the inflation plot is pretty simple.
I’m hearing that folks have been invited to speak at the upcoming Rstudio conference. Congratulations to the folks who got accepted this year. I am not sure if I’m going to go to the conference this year, but I recommend you consider it if you love R. I spoke there last year, giving an E-Poster. It was a lot of fun. The best part was getting a chance to meet other R enthusiasts.
I’ve been thinking about smoothing time series data. I tweeted out a bite size bit of code. To fit it into a tweet, I had to squeeze things down a bit. Slightly more verbose, and using fredr to get data from FRED using their API. You’ll need an API key from FRED. These data happen to be for New Private Housing Units Authorized by Building Permits - in Structures with 1 Unit.
Early last Friday morning I was sitting in Palm Springs International Airport waiting to catch a flight back to Virginia. I had traveled out west to speak at the 2019 NAGLREP Conference. This Friday happened to be jobs Friday, when the U.S. Bureau of Labor Statistics releases the employment situation. Jobs Fridays are busy on Twitter. Everybody seems eager to offer a perspective on what the latest jobs numbers mean for the U.