A blog by Rob J Hyndman 

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Coherent population forecasting using R

Published on 24 July 2014

This is an exam­ple of how to use the demog­ra­phy pack­age in R for sto­chas­tic pop­u­la­tion fore­cast­ing with coher­ent com­po­nents. It is based on the papers by Hyn­d­man and Booth (IJF 2008) and Hyn­d­man, Booth and Yas­meen (Demog­ra­phy 2013). I will use Aus­tralian data from 1950 to 2009 and fore­cast the next 50 years.

In demog­ra­phy, “coher­ent” fore­casts are where male and females (or other sub-​​groups) do not diverge over time. (Essen­tially, we require the dif­fer­ence between the groups to be sta­tion­ary.) When we wrote the 2008 paper, we did not know how to con­strain the fore­casts to be coher­ent in a func­tional data con­text and so this was not dis­cussed. My later 2013 paper pro­vided a way of impos­ing coher­ence. This blog post shows how to imple­ment both ideas using R. (more…)

 
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Plotting the characteristic roots for ARIMA models

Published on 23 July 2014

When mod­el­ling data with ARIMA mod­els, it is some­times use­ful to plot the inverse char­ac­ter­is­tic roots. The fol­low­ing func­tions will com­pute and plot the inverse roots for any fit­ted ARIMA model (includ­ing sea­sonal mod­els). (more…)

 
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I am not an econometrician

Published on 21 July 2014

I am a sta­tis­ti­cian, but I have worked in a depart­ment of pre­dom­i­nantly econo­me­tri­cians for the past 17 years. It is a lit­tle like an Aus­tralian vis­it­ing the United States. Ini­tially, it seems that we talk the same lan­guage, do the same sorts of things, and have a very sim­i­lar cul­ture. But the longer you stay there, the more you realise there are dif­fer­ences that run deep and affect the way you see the world.

Last week at my research group meet­ing, I spoke about some of the dif­fer­ences I have noticed. Coin­ci­den­tally, Andrew Gel­man blogged about the same issue a day later. (more…)

 
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Variations on rolling forecasts

Published on 16 July 2014

Rolling fore­casts are com­monly used to com­pare time series mod­els. Here are a few of the ways they can be com­puted using R. I will use ARIMA mod­els as a vehi­cle of illus­tra­tion, but the code can eas­ily be adapted to other uni­vari­ate time series mod­els. (more…)

 
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SAS/​IIF grants

Published on 15 July 2014

Every year, the Inter­na­tional Insti­tute of Fore­cast­ers in con­junc­tion with SAS offer some small grants to help pro­mote research in fore­cast­ing. There are two $5000 grants per year for research on fore­cast­ing method­ol­ogy and appli­ca­tions. This year, appli­ca­tions close on 30 Sep­tem­ber 2014. More details are given here.

Infor­ma­tion about past SAS-​​IIF awards is given on the IIF web­site. It is inter­est­ing to see the range of top­ics cov­ered. Here are the win­ning projects in the last two years:

  • Jef­frey Stone­braker: “Prob­a­bilis­tic Fore­cast­ing of the Global Demand for the Treat­ment of Hemo­philia B.”
  • Yongchen (Her­bert) Zhao: “Robust Real-​​Time Auto­mated Fore­cast Com­bi­na­tion in SAS: Devel­op­ment of a SAS Pro­ce­dure and a Com­pre­hen­sive Eval­u­a­tion of Recently Devel­oped Com­bi­na­tion Methods.”
  • Zoe Theocharis, Nigel Har­vey, Leonard Smith: “Improv­ing judg­men­tal input to hur­ri­cane fore­casts in the insur­ance and rein­sur­ance sector.”
  • Elena-​​Ivona Dumitrescu, Janine Chris­tine Bal­ter, Peter Rein­hard Hansen: “Fore­cast­ing Exchange Rate Volatil­ity: Mul­ti­vari­ate Real­ized GARCH Framework.”
  • Yorghos Tripodis: “Fore­cast­ing the Cog­ni­tive Sta­tus in an Aging Population.”
 
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Varian on big data

Published on 16 June 2014

Last week my research group dis­cussed Hal Varian’s inter­est­ing new paper on “Big data: new tricks for econo­met­rics”, Jour­nal of Eco­nomic Per­spec­tives, 28(2): 3–28.

It’s a nice intro­duc­tion to trees, bag­ging and forests, plus a very brief entrée to the LASSO and the elas­tic net, and to slab and spike regres­sion. Not enough to be able to use them, but ok if you’ve no idea what they are. (more…)

 
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Specifying complicated groups of time series in hts

Published on 15 June 2014

With the lat­est ver­sion of the hts pack­age for R, it is now pos­si­ble to spec­ify rather com­pli­cated group­ing struc­tures rel­a­tively easily.

All aggre­ga­tion struc­tures can be rep­re­sented as hier­ar­chies or as cross-​​products of hier­ar­chies. For exam­ple, a hier­ar­chi­cal time series may be based on geog­ra­phy: coun­try, state, region, store. Often there is also a sep­a­rate prod­uct hier­ar­chy: prod­uct groups, prod­uct types, packet size. Fore­casts of all the dif­fer­ent types of aggre­ga­tion are required; e.g., prod­uct type A within region X. The aggre­ga­tion struc­ture is a cross-​​product of the two hierarchies.

This frame­work includes even appar­ently non-​​hierarchical data: con­sider the sim­ple case of a time series of deaths split by sex and state. We can con­sider sex and state as two very sim­ple hier­ar­chies with only one level each. Then we wish to fore­cast the aggre­gates of all com­bi­na­tions of the two hierarchies.

Any num­ber of sep­a­rate hier­ar­chies can be com­bined in this way. Non-​​hierarchical fac­tors such as sex can be treated as single-​​level hier­ar­chies. (more…)

 
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European talks. June-​​July 2014

Published on 14 June 2014

For the next month I am trav­el­ling in Europe and will be giv­ing the fol­low­ing talks.

17 June. Chal­lenges in fore­cast­ing peak elec­tric­ity demand. Energy Forum, Sierre, Valais/​Wallis, Switzerland.

20 June. Com­mon func­tional prin­ci­pal com­po­nent mod­els for mor­tal­ity fore­cast­ing. Inter­na­tional Work­shop on Func­tional and Oper­a­to­r­ial Sta­tis­tics. Stresa, Italy.

24–25 June. Func­tional time series with appli­ca­tions in demog­ra­phy. Hum­boldt Uni­ver­sity, Berlin.

1 July. Fast com­pu­ta­tion of rec­on­ciled fore­casts in hier­ar­chi­cal and grouped time series. Inter­na­tional Sym­po­sium on Fore­cast­ing, Rot­ter­dam, Netherlands.

 
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Creating a handout from beamer slides

Published on 11 June 2014

I’m about to head off on a speak­ing tour to Europe (more on that in another post) and one of my hosts has asked for my pow­er­point slides so they can print them. They have made two false assump­tions: (1) that I use pow­er­point; (2) that my slides are sta­tic so they can be printed.

Instead, I pro­duced a cut-​​down ver­sion of my beamer slides, leav­ing out some of the ani­ma­tions and other fea­tures that will not print eas­ily. Then I pro­duced a pdf file with sev­eral slides per page. (more…)

 
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Data science market places

Published on 26 May 2014

Some new web­sites are being estab­lished offer­ing “mar­ket places” for data sci­ence. Two I’ve come across recently are Experfy and Sna­p­An­a­lytx. (more…)

 
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