CPAT and the Rényi-Type Statistic; End-of-Sample Change Point Detection in R

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Introduction

I started my first research project as a graduate student when I was only in the MSTAT program at the University of Utah, at the very end of 2015 (or very beginning of 2016; not sure exactly when) with my current advisor, Lajos Horváth. While I am disappointed it took this long, I am glad to say that the project is finished and I am finally published.

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Organizing R Research Projects: CPAT, A Case Study

Introduction

Months ago, I asked a question to the community: how should I organize my R research projects? After writing that post, doing some reading, then putting a plan in practice, I now have my own answer.

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Problems in Estimating GARCH Parameters in R (Part 2; rugarch)

Introduction

Now here is a blog post that has been sitting on the shelf far longer than it should have. Over a year ago I wrote an article about problems I was having when estimating the parameters of a GARCH(1,1) model in R. I documented the behavior of parameter estimates (with a focus on \beta) and perceived pathological behavior when those estimates are computed using fGarch. I called for help from the R community, including sending out the blog post over the R Finance mailing list.

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Time to Accept It: publishing in the Journal of Statistical Software

I’m reblogging this article mostly for myself. If you’ve been following my blog, you’ll see that recently I published an article on organizing R code that mentioned using packages to organize that code. One of the advantages of doing so is that the work you’ve done is easily distributed. If the methods are novel in some way, you may even get a paper in J. Stat. Soft. or the R Journal that helps people learn how to use your software and exposes the methodology to a wider audience. Therefore we should know something about those journals. (I recently got a good reply on Reddit about the difference between these journals.)

The Geokook.

When I was considering submitting my paper on psd to J. Stat. Soft. (JSS), I kept noticing that the time from “Submitted” to “Accepted” was nearly two years in many cases.  I ultimately decided that was much too long of a review process, no matter what the impact factor might be (and in two years time, would I even care?).  Tonight I had the sudden urge to put together a dataset of times to publication.

Fortunately the JSS website is structured such that it only took a few minutes playing with XML scraping (*shudder*) to write the (R) code to reproduce the full dataset.  I then ran a changepoint (published in JSS!) analysis to see when shifts in mean time have occurred.  Here are the results:

Top: The number of days for a paper to go from 'Submitted' to 'Accepted'.  Middle: In log2(time), with lines for one month, one year, and two years. Bottom frame: changepoint analyses. Top: The number of days for a paper to go from ‘Submitted’ to ‘Accepted’ as a function of the cumulative issue index (each paper is an “issue”…

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How Should I Organize My R Research Projects?

My formal training in computer programming consists of two R programming labs required by my first statistics classes, and some JavaScript and database training. That’s about it. Most of my programming knowledge is self-taught.1 For a researcher who does a lot of programming but doesn’t consider programming to be the job, that’s fine… up to a point.

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Replication Intervals

At the University of Utah I’ve taught MATH 1070 and MATH 3070. Both are introductory statistics classes, but I call MATH 1070 “Introductory Statistics for People Who Don’t Like Math” while MATH 3070 is “Introductory Statistics for People Who Do Like Math”, since the latter requires calculus and uses far more probability. In both classes, though, students need to learn what confidence intervals (CIs) say and don’t say, and I spend a lot of time debunking common misconceptions for what a confidence interval says.

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