Abstract
The application of cutting-edge statistical methodology is limited by the capabilities of the systems in which it is implemented. In particular, the limitations of R mean that applications developed there do not scale to the larger problems of interest in practice. We identify some of the limitations of the computational model of the R language that reduces its effectiveness for dealing with large data efficiently in the modern era.
We propose developing an R-like language on top of a Lisp-based engine for statistical computing that provides a paradigm for modern challenges and which leverages the work of a wider community. At its simplest, this provides a convenient, high-level language with support for compiling code to machine instructions for very significant improvements in computational performance. But we also propose to provide a framework which supports more computationally intensive approaches for dealing with large datasets and position ourselves for dealing with future directions in high-performance computing.
We discuss some of the trade-offs and describe our efforts to realizing this approach. More abstractly, we feel that it is important that our community explore more ambitious, experimental and risky research to explore computational innovation for modern data analyses.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
BRUN, R. and RADEMAKERS, F. (1997): ROOT - An Object Oriented Data Analysis Framework, Nucl. Inst. & Meth. in Phys. Res. A, 389, 81–86. (Proceedings AIHENP ’96 Workshop.)
HARMON, C. (2007): rsbcl - An Interface Between R and Steel Bank Common Lisp. Personal communication.
TIERNEY, L. (2001): Compiling R: A Preliminary Report, DSC 2001 Proceedings of the 2nd International Workshop on Distributed Statistical Computing.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2008 Physica-Verlag Heidelberg
About this paper
Cite this paper
Ihaka, R., Lang, D.T. (2008). Back to the Future: Lisp as a Base for a Statistical Computing System. In: Brito, P. (eds) COMPSTAT 2008. Physica-Verlag HD. https://doi.org/10.1007/978-3-7908-2084-3_2
Download citation
DOI: https://doi.org/10.1007/978-3-7908-2084-3_2
Publisher Name: Physica-Verlag HD
Print ISBN: 978-3-7908-2083-6
Online ISBN: 978-3-7908-2084-3
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)