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Introduction

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Coding Ockham's Razor
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Abstract

This book is about inductive inference using the minimum message length (MML) principle and a computer. It is accompanied by a library of software to help an applications programmer, student or researcher in the fields of data analysis or machine learning to write computer programs of this kind.

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Notes

  1. 1.

    OED.

  2. 2.

    Marilyn vos Savant.

  3. 3.

    OED.

  4. 4.

    This textual packaging of a UPModel.M and a UPModel.Est inside a UPModel is simply convenient, often. It is not compulsory.

  5. 5.

    David [22] attributes the “first (?) occurrence” of the term “information matrix” to Fisher [31, p.184].

References

  1. T. Bayes, An essay towards solving a problem in the doctrine of chances. Philos. Trans. 370–418 (1763). http://www.jstor.org/stable/2333180

  2. D.M. Boulton, C.S. Wallace, The information content of a multistate distribution. J. Theor. Biol. 23(2), 269–278 (1969). https://doi.org/10.1016/0022-5193(69)90041-1

    Article  MathSciNet  Google Scholar 

  3. G.E.P. Box, Robustness in the strategy of scientific model building. Robustness Stat. 1, 201–236 (1979). https://doi.org/10.1016/B978-0-12-438150-6.50018-2. Includes, “All models are wrong but some are useful”

  4. J.H. Conway, N.J.A. Sloane, Sphere Packings, Lattices and Groups (Springer, Berlin, 1988). ISBN 978-0387966175. https://doi.org/10.1007/978-1-4757-6568-7

    Book  Google Scholar 

  5. H.A. David, First (?) occurrence of common terms in mathematical statistics. Am. Stat. 49(2), 121–133 (1995). https://doi.org/10.2307/2684625. http://www.jstor.org/stable/2684625

    MathSciNet  Google Scholar 

  6. G.E. Farr, C.S. Wallace, The complexity of strict minimum message length inference. Comput. J. 45(3), 285–292 (2002). https://doi.org/10.1093/comjnl/45.3.285

    Article  Google Scholar 

  7. R.A. Fisher, The negative binomial distribution. Ann. Eugenics 11(1), 182–187 (1941). https://doi.org/10.1111/j.1469-1809.1941.tb02284.x. David (First (?) occurrence of common terms in mathematical statistics. Am. Stat. 49(2), 121–133 (1995). https://doi.org/10.2307/2684625. http://www.jstor.org/stable/2684625) attributes the “first (?) occurrence” of the term “information matrix” to this paper

    Article  MathSciNet  Google Scholar 

  8. J.-L. Gailly, M. Adler, gzip (2003). http://www.gzip.org/

  9. S. Kullback, R.A. Leibler, On information and sufficiency. Ann. Math. Stat. 22(1), 79–86 (1951). https://doi.org/10.1214/aoms/1177729694

    Article  MathSciNet  Google Scholar 

  10. P.S. Laplace, Mémoire sur la probabilité des causes par les évènemens (1774). https://projecteuclid.org/download/pdf_1/euclid.ss/1177013621. Translated by S. M. Stigler (1986) (Laplace’s 1774 memoir on inverse probability. Stat. Sci. 1(3), 359–363 (1986). https://projecteuclid.org/download/pdf_1/euclid.ss/1177013620)

  11. G.R.G. Mure, Aristotle’s posterior analytics, in Aristotle Organon and Other Works, ed. by W.D. Ross (1925). https://archive.org/details/AristotleOrganon

  12. R.C. Pasco, Source coding algorithms for fast data compression. PhD thesis, Stanford University CA, 1976

    Google Scholar 

  13. J. Rissanen, Generalized kraft inequality and arithmetic coding. IBM J. Res. Dev. 20(3), 198–203 (1976). https://doi.org/10.1147/rd.203.0198

    Article  MathSciNet  Google Scholar 

  14. C.E. Shannon, A mathematical theory of communication. Bell Labs Tech. J. 27(3,4), 379–423, 623–656 (1948). https://doi.org/10.1002/j.1538-7305.1948.tb01338.x

    Article  MathSciNet  Google Scholar 

  15. P.V. Spade (ed.), The Cambridge Companion to Ockham (Cambridge University Press, Cambridge, 1999). ISBN 978-0521582445. https://doi.org/10.1017/CCOL052158244X

    MATH  Google Scholar 

  16. S.M. Stigler, Laplace’s 1774 memoir on inverse probability. Stat. Sci. 1(3), 359–363 (1986). https://projecteuclid.org/download/pdf_1/euclid.ss/1177013620. Introduction to translation of Laplace (Mémoire sur la probabilité des causes par les évènemens (1774). https://projecteuclid.org/download/pdf_1/euclid.ss/1177013621. Translated by S. M. Stigler (1986) (Laplace’s 1774 memoir on inverse probability. Stat. Sci. 1(3), 359–363 (1986). https://projecteuclid.org/download/pdf_1/euclid.ss/1177013620)) pp.364–378 same issue

    Article  MathSciNet  Google Scholar 

  17. C.S. Wallace, Statistical and Inductive Inference by Minimum Message Length (Springer, Berlin, 2005). ISBN 978-0-387-23795-4. https://doi.org/10.1007/0-387-27656-4

    MATH  Google Scholar 

  18. C.S. Wallace, D.M. Boulton, An information measure for classification. Comput. J. 11(2), 185–194 (1968). https://doi.org/10.1093/comjnl/11.2.185

    Article  Google Scholar 

  19. C.S. Wallace, D.M. Boulton, An invariant Bayes method for point estimation. Classif. Soc. Bull. 3(3), 11–34 (1975)

    Google Scholar 

  20. C.S. Wallace, P.R. Freeman, Estimation and inference by compact coding. J. R. Stat. Soc. Ser. B Methodol. 240–265 (1987). http://www.jstor.org/stable/2985992

  21. P. Zador, Asymptotic quantization error of continuous signals and the quantization dimension. IEEE Trans. Inf. Theory 28(2), 139–149 (1982). https://doi.org/10.1109/TIT.1982.1056490

    Article  MathSciNet  Google Scholar 

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Allison, L. (2018). Introduction. In: Coding Ockham's Razor. Springer, Cham. https://doi.org/10.1007/978-3-319-76433-7_1

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  • DOI: https://doi.org/10.1007/978-3-319-76433-7_1

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