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Empirical data sets are algorithmically compressible: reply to McAllister?

Abstract: James McAllister’s 2003 article, ‘Algorithmic randomness in empirical data’, claims that empirical data sets are algorithmically random, and hence incompressible. We show that this claim is mistaken. We present theoretical arguments and empirical evidence for compressibility, and discuss t...

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Published in:Studies in History & Philosophy of Science Part A Vol. 36; no. 2; pp. 391 - 403
Main Authors: Twardy, Charles, Gardner, Steve, Dowe, David L.
Format: Editorial
Published: Elsevier B.V. Jun2005
Subjects:
Algorithms
McAllister, James
Minimum message length (Information theory)
Algebra
Online Access:View this record in EBSCOhost
Summary:Abstract: James McAllister’s 2003 article, ‘Algorithmic randomness in empirical data’, claims that empirical data sets are algorithmically random, and hence incompressible. We show that this claim is mistaken. We present theoretical arguments and empirical evidence for compressibility, and discuss the matter in the framework of Minimum Message Length (MML) inference.