Ihaka lectures 2017: Statistical computing in a (more) static environment Event as iCalendar

(Science Event Tags, Conferences, Lectures, Seminars, Department of Statistics)

29 March 2017


Venue: MLT1 Lecture Theatre, Ground Floor, Building 303, 38 Princes Street, City Campus, Auckland Central

Location: Please join us for refreshments from 6pm in the foyer area of Building 302, 23 Symonds Street

Host: Department of Statistics

Cost: Free - all welcome

Website: www.stats.auckland.ac.nz/ihaka-lectures

Speaker: Associate Professor Ross Ihaka, Department of Statistics, University of Auckland


Associate Professor Ross Ihaka
Associate Professor Ross Ihaka

In the final lecture in the 2017 Ihaka Lecture Series Associate Professor Ross Ihaka (Department of Statistics, University of Auckland) will deliver the following:


Statistical computing in a (more) static environment (Ross Ihaka & Brendan McArdle)

Ten years ago, Duncan Temple Lang (perhaps jokingly) accused the creators of R of being guilty of “killing research in statistical computing”. Although appearing exaggerated at the time, the statement has turned out to be prophetic. Much of what passes for statistical computing research these days consists of little more than writing ‘R packages’. While there may be some merit in this kind of activity, research at a more fundamental level is desperately needed. This talk is concerned with that deeper level.

Statistical computing systems exist on a spectrum. From the very dynamic at one end, to the very static at the other. Dynamic systems (like R, S or LispStat) provide a very flexible computing environment but the price for this flexibility is performance. A lot is known about the dynamic type of system but only limited experience has been gained at the static end of the spectrum. In particular, not much is known about the flexibility/performance trade-off and whether more static systems can provide sufficient flexibility to justify their (potentially) improved performance. This talk will look at some of the problems associated with implementing a more static statistical computing environment.

Lecture commences at 6.30pm in MLT1, Building 303, 38 Princes Street.

Please join us for refreshments from 6pm in the foyer area of Building 302, 23 Symonds Street.



Ross Ihaka is an Associate Professor of Statistics at the University of Auckland. Ross and Robert Gentleman were the originators of the R statistical software system. Ross’s research interests include statistical computing research and exposition, and also statistical graphics and visualisation.


Find out more information on the Ihaka Lecture Series 2017.


If you cannot attend the lecture, you can watch it live on Wednesday 29 March from 6.30pm at the link below: