Hyndsight

 

A blog by Rob J Hyndman 

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IJF quality indicators

Published on 17 May 2013

I often receive email ask­ing about IJF qual­ity indi­ca­tors. Here is one I received today.

Dear Pro­fes­sor Hyndman,

I recently had a paper pub­lished in IJF enti­tled, “xxxxxxxxxxxx”. I am very pleased with the pub­li­ca­tion and con­sider IJF to be an excel­lent out­let for my work in time-​​series econometrics.

I have an unusual request, but I hope you will con­sider respond­ing. My research is judged by non-​​economists and IJF is not on their list of “qual­ity” jour­nals. It makes a sig­nif­i­cant dif­fer­ence in my research rat­ing and pay. Would you mind send­ing some objec­tive infor­ma­tion re the qual­ity of IJF that I can pass along to the committee?

And here is part of my reply:

  • The IJF is ranked A in Aus­tralia (we have four lev­els — A*, A, B and C).†
  • The IJF 2011 2-​​year impact fac­tor is 1.485. In 2010 it was 1.863. The five year impact fac­tor is 2.450. Com­pare this to the Jour­nal of Busi­ness and Eco­nomic Sta­tis­tics which has a 2-​​year impact fac­tor of 1.693, or Com­pu­ta­tional Sta­tis­tics & Data Analy­sis with 1.089.
  • We are ranked 40 out of 305 eco­nom­ics jour­nals based on our 2-​​year impact factor.
  • We receive about 400 sub­mis­sions annu­ally, and pub­lish about 70 per year. But that includes invited papers. Of the con­tributed papers, we reject about 85–90%.

† The Aus­tralian rank­ings were pro­duced by the Aus­tralian Research Coun­cil a few years ago after exten­sive con­sul­ta­tion. They were later dropped, but the rank­ings are still fre­quently cited and used to mea­sure jour­nal qual­ity. Although the ARC no longer has the rank­ings on their web­site, they are avail­able here. Also use­ful is the list of econo­met­rics jour­nals (includ­ing the IJF), and the list of sta­tis­tics jour­nals.

 
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Forecasting annual totals from monthly data

Published on 15 May 2013

This ques­tion was posed on cross​val​i​dated​.com:

I have a monthly time series (for 2009–2012 non-​​stationary, with sea­son­al­ity). I can use ARIMA (or ETS) to obtain point and inter­val fore­casts for each month of 2013, but I am inter­ested in fore­cast­ing the total for the whole year, includ­ing pre­dic­tion inter­vals. Is there an easy way in R to obtain inter­val fore­casts for the total for 2013?

I’ve come across this prob­lem before in my con­sult­ing work, although I don’t think I’ve ever pub­lished my solu­tion. So here it is. (more…)

 
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Establishing priority

Published on 6 May 2013

The nature of research is that other peo­ple are prob­a­bly work­ing on sim­i­lar ideas to you, and it is pos­si­ble that some­one will beat you to pub­lish­ing them. (more…)

 
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Colors in LaTeX

Published on 6 May 2013

This is a guest post by Rico Mag­nucki from Span­DeX

Intro­duc­tion

Try­ing to high­light some­thing, you may reach a point where bold or ital­ics writ­ten text is not enough. In sit­u­a­tions like these, col­ors can be very help­ful. Like every writ­ing tool, LaTeX has some pos­si­bil­i­ties to deal with it. At first you need to include a package.

\usepackage{xcolor}

You may won­der why we’re using xcolor and not color. It is com­mon prac­tice to recre­ate pack­ages with new func­tion­al­i­ties and call it “extended ver­sion”. There­fore xcolor is an extended ver­sion of color.

So what are the key ele­ments of using color with LaTeX? In this Tuto­r­ial we will show you how to col­orize strings, high­light text and cre­ate framed color boxes. (more…)

 
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My new forecasting book is finally finished

Published on 21 April 2013

My new online fore­cast­ing book (writ­ten with George Athana­sopou­los) is now com­pleted. I pre­vi­ously described it on this blog nearly a year ago.

In real­ity, an online book is never com­plete, and we plan to con­tin­u­ally update it. But it is now at the point where it is suit­able for course work, and con­tains exer­cises and references.

We hope that users (espe­cially other lec­tur­ers) will sub­mit mate­ri­als such as slides and exer­cises, that can be shared on the website.

For those want­ing a print ver­sion, we will be sell­ing it via Ama­zon in the next few months. The online ver­sion will remain freely available.

If other authors are inter­ested in this pub­lish­ing model, please see this page. The book is being pub­lished by OTexts, a new inno­v­a­tive pub­lish­ing com­pany I am estab­lish­ing. The fore­cast­ing book is our first pub­li­ca­tion, but we have three oth­ers that should be online within the next month or two. 

 
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George E P Box (1919−2013)

Published on 31 March 2013

Last Thurs­day (28 March 2013), George Box passed away at the age of 93. He was one of the great sta­tis­ti­cians of the last 100 years, and leaves an aston­ish­ingly diverse legacy.

When I teach fore­cast­ing to my sec­ond year com­merce stu­dents, we cover Box-​​Cox trans­for­ma­tions, Box-​​Pierce and Ljung-​​Box tests, and Box-​​Jenkins mod­el­ling, and my stu­dents won­der if it is the same Box in all cases. It is. And we don’t even go near his work on response sur­face mod­el­ling, design of exper­i­ments, qual­ity con­trol or ran­dom num­ber gen­er­a­tion. Occa­sion­ally, a stu­dent won­ders if box­plots are also due to GEP Box, but they were the brain­child of his good friend John W Tukey.

I often quote Box’s famous words to my stu­dents “All mod­els are wrong but some are use­ful” (Box, GEP, 1979, Robust­ness in the strat­egy of sci­en­tific model build­ing, Robust­ness in Sta­tis­tics, Aca­d­e­mic Press, pp.201–236.) This sum­marises my view of sta­tis­ti­cal mod­el­ling per­fectly — no-​​one should believe their mod­els; instead, treat them as tools to be used to assist in under­stand­ing the data. (more…)

 
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The difference between prediction intervals and confidence intervals

Published on 13 March 2013

Pre­dic­tion inter­vals and con­fi­dence inter­vals are not the same thing. Unfor­tu­nately the terms are often con­fused, and I am often fre­quently cor­rect­ing the error in stu­dents’ papers and arti­cles I am review­ing or editing.

A pre­dic­tion inter­val is an inter­val asso­ci­ated with a ran­dom vari­able yet to be observed, with a spec­i­fied prob­a­bil­ity of the ran­dom vari­able lying within the inter­val. For exam­ple, I might give an 80% inter­val for the fore­cast of GDP in 2014. The actual GDP in 2014 should lie within the inter­val with prob­a­bil­ity 0.8. Pre­dic­tion inter­vals can arise in Bayesian or fre­quen­tist statistics.

A con­fi­dence inter­val is an inter­val asso­ci­ated with a para­me­ter and is a fre­quen­tist con­cept. The para­me­ter is assumed to be non-​​random but unknown, and the con­fi­dence inter­val is com­puted from data. Because the data are ran­dom, the inter­val is ran­dom. A 95% con­fi­dence inter­val will con­tain the true para­me­ter with prob­a­bil­ity 0.95. That is, with a large num­ber of repeated sam­ples, 95% of the inter­vals would con­tain the true para­me­ter. (more…)

 
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ETS models now in EViews 8

Published on 1 March 2013

The ETS mod­el­ling frame­work devel­oped in my 2002 IJF paper (with Koehler, Sny­der and Grose), and in my 2008 Springer book (with Koehler, Ord and Sny­der), is now avail­able in EViews 8. I had no idea they were even work­ing on it, so it was quite a sur­prise to be told that EViews now includes ETS mod­els. (more…)

 
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Tools for LaTeX tables

Published on 28 February 2013

This is a guest post by Gre­gori Kanatzidis from Span­DeX.

Tables are a tricky busi­ness in LaTeX. Tables typ­i­cally have their own for­mat­ting, and worse, are usu­ally cre­ated in other appli­ca­tions. The com­mands and pack­ages pro­vided with LaTeX go some ways to mak­ing tables eas­ier to use, but the clunky nature of the syn­tax make tables one of the worst parts of for­mat­ting a doc­u­ment. In this post, I’ll go over some of the draw­backs of LaTeX tables, and some tools that exist to make work­ing with tables in LaTeX a bit eas­ier. (more…)

 
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Removing white space around R figures

Published on 22 February 2013

When I want to insert fig­ures gen­er­ated in R into a LaTeX doc­u­ment, it looks bet­ter if I first remove the white space around the fig­ure. Unfor­tu­nately, R does not make this easy as the graphs are gen­er­ated to look good on a screen, not in a document.

There are two things that can be done to fix this prob­lem. (more…)

 
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