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Tuesday, June 28 • 1:36pm - 1:54pm
What can R learn from Julia

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Julia, like R, is a dynamic language for scientific computing but, unlike R, it was explicitly designed to deliver performance competitive to traditional batch-compiled languages. To achieve this Julia's designers made a number of unusual choices, including the presence of a set of type annotations that are used for dispatching methods and speed up code, but not for type-checking. The result is that many Julia programs are competitive with equivalent programs written in C. This talk gives a brief overview of the key points of Julia's design and considers whether similar ideas could be adopted in R.

Moderators
avatar for Ioannis  Kosmidis

Ioannis Kosmidis

Associate Professor, Department of Statistical Science, University College London
I am a Senior Lecturer at the Department of Statistical Science in University College London. My theoretical and methodological research focuses on optimal estimation and inference from complex statistical models, penalized likelihood methods and clustering. A particular focus of my work is the development of efficient, in terms of computational complexity and implementation, algorithms for applying the methods I develop to prominent... Read More →

Speakers
JV

Jan Vitek

Northeastern University


Attendees (143)