Julia for Statisticians

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Sponsored by the ARC Centre of excellence for Mathematical and Statistical Frontiers (http://acems.org.au)


About the Course

Julia is a new high-performance dynamic language for technical computing. Its central aim is to solve “two language problems”, whereby an initial program is written in a convenient dynamic language, but then the computationally demanding parts need to be re-written in a lower-level language. By heavily exploiting features such as just-in-time (JIT) compilation and multiple dispatch, Julia is able to achieve performance comparable to statically-compiled languages such as C or Fortran, yet have the convenience of a dynamic language such as Python or R. Julia is open source and freely available under a permissive MIT licence.

The aim of this course is to provide an introduction to Julia that would be of interest to statisticians. It will provide a solid introduction to the syntax and core ideas to the language, such as types, generic functions and macros, as well as general guidance for writing high-performance code. It will then aim to cover some of the features that are likely to be of interest to statisticians, such as statistics libraries, plotting and graphics functionality, as well as interfacing with other languages such as R, Python and C.



The course is primarily aimed at those who have some programming experience in a similar high-level language such as R, Python or Matlab.
About the Instructor

Simon Byrne received Bachelor of Commerce/Bachelor of Science in 2004 and a Bachelor of Science (Honours) in Mathematics in 2005 from Macquarie University. He has worked in the insurance industry, and completed his PhD in Statistics at the University of Cambridge in 2011. He is currently an EPSRC Research Fellow in the Department of Statistical Science, University College London.simonbyrne

He has been contributing to the Julia language since 2012, and the developer of several packages, including the Distributions, KernelDensity and RCall packages.



Course Preparation

Attendees should bring a laptop with the latest version of Julia (0.4) installed, available from http://julialang.org/downloads/. The course will primarily be taught using the interactive IJulia environment. It would be useful to try to install this ahead of time by running Pkg.add(“IJulia”).

Alternatively, those with a Google account can use an online hosted installation at https://www.juliabox.org/.


Course fees:

Payment before 10 November 2015   Payment from 10 November 2015
SSAI/ACEMS Students: $75.00 $150.00
Other students: $120.00 $200.00
SSAI/ACEMS Members (non-students): $150.00 $250.00
General fee: $250.00 $350.00

SSAI Student Membership is available for $20 p/a

There are only 25 places available for this workshop, so please book early to avoid disappointment.

Registrations close on Thursday, 12 November 2015 or earlier if the course is booked out.



8:30am: Registrations open (tea and coffee available)

9:00am: Workshop begins

10:30am:  Morning tea

1.00pm: End of workshop, followed by a light lunch (provided)


Travel Expenses

Occasionally workshops have to be cancelled due to a lack of subscription. Early registration ensures that this will not happen. Please contact the SSAI Office before making any travel arrangements to confirm that the workshop will go ahead, because the SSAI will not be held responsible for any travel or accommodation expenses incurred due to a workshop cancellation.


Cancellation Policy

Cancellations received prior to 10 November 2015 will be refunded in full. Confirmation of the refund having been processed will be emailed. Should additional documentation pertaining to the refund be required, a $20 administration fee will be charged.

From 10 November 2015 no part of the registration fee will be refunded. However, registrations are transferable within the same organisation. Please advise any changes to [email protected].


Julia for Statisticians
When: 17/11/2015
Time: 9:30 am - 1:00 pm
Cost: from $75.00 (SSAI/ACEMS students)
Location: University of Technology Sydney,
638 Jones Street,
NSW 2007

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