Statistical modelling and analysis of big data

I’m cur­rently attend­ing the one day work­shop on this topic at QUT in Bris­bane. This morn­ing I spoke on “Visu­al­iz­ing and fore­cast­ing big time series data”. My slides are here.

The talks are being streamed.


Big data is now endemic in busi­ness, indus­try, gov­ern­ment, envi­ron­men­tal man­age­ment, med­ical sci­ence, social research and so on. One of the com­men­su­rate chal­lenges is how to effec­tively model and analyse these data.

This work­shop will bring together national and inter­na­tional experts in sta­tis­ti­cal mod­el­ling and analy­sis of big data, to share their expe­ri­ences, approaches and opin­ions about future direc­tions in this field.

IASC Data Analysis Competition 2015

The Inter­na­tional Asso­ci­a­tion for Sta­tis­ti­cal Com­put­ing (IASC) is hold­ing a Data Analy­sis Com­pe­ti­tion. Win­ners will be invited to present their work at the Joint Meet­ing of IASC-​​ABE Satel­lite Con­fer­ence for the 60th ISI WSC 2015 to be held at Atlân­tico Búzios Con­ven­tion & Resort in Búzios, RJ, Brazil (August 2–4, 2015). They will also be invited to sub­mit a man­u­script for pos­si­ble pub­li­ca­tion (fol­low­ing peer review) to IASC’s offi­cial jour­nal, Com­pu­ta­tional Sta­tis­tics & Data Analy­sis. Con­tinue reading →

Prediction competitions

Com­pe­ti­tions have a long his­tory in fore­cast­ing and pre­dic­tion, and have been instru­men­tal in forc­ing research atten­tion on meth­ods that work well in prac­tice. In the fore­cast­ing com­mu­nity, the M com­pe­ti­tion and M3 com­pe­ti­tion have been par­tic­u­larly influ­en­tial. The data min­ing com­mu­nity have the annual KDD cup which has gen­er­ated atten­tion on a wide range of pre­dic­tion prob­lems and asso­ci­ated meth­ods. Recent KDD cups are hosted on kag­gle.

In my research group meet­ing today, we dis­cussed our (lim­ited) expe­ri­ences in com­pet­ing in some Kag­gle com­pe­ti­tions, and we reviewed the fol­low­ing two papers which describe two pre­dic­tion competitions:

  1. Athana­sopou­los and Hyn­d­man (IJF 2011). The value of feed­back in fore­cast­ing com­pe­ti­tions. [preprint ver­sion]
  2. Roy et al (2013). The Microsoft Aca­d­e­mic Search Dataset and KDD Cup 2013.

Con­tinue reading →