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  1. Simplicity, Inference and Modelling: Keeping It Sophisticatedly Simple.Arnold Zellner, Hugo A. Keuzenkamp & Michael McAleer (eds.) - 2001 - New York: Cambridge University Press.
    The idea that simplicity matters in science is as old as science itself, with the much cited example of Ockham's Razor, 'entia non sunt multiplicanda praeter necessitatem': entities are not to be multiplied beyond necessity. A problem with Ockham's razor is that nearly everybody seems to accept it, but few are able to define its exact meaning and to make it operational in a non-arbitrary way. Using a multidisciplinary perspective including philosophers, mathematicians, econometricians and economists, this 2002 monograph examines simplicity (...)
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  • Note on simplicity and statistical explanations of correlations.Chrysovalantis Stergiou - manuscript
    In this note, I discuss the simplicity of rival statistical explanations of a correlation, couched in terms of Reichenbachian Common Cause Systems. Simplicity is analyzed in two components, the so-called intrinsic and contextual simplicity. I show that if one disentangles simplicity from explanatory power then the size of the system provides an adequate for simplicity in both of its dimensions.
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