Erratum to: Model change and methodological virtues in scientific inference

Synthese 191 (14):3469-3472 (2014)
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Abstract

Erratum to: Synthese DOI 10.1007/s11229-014-0408-3Appendix 1: NotationLet \(X\) represent a sequence of data, and let \(X_B^t\) represent an i.i.d. subsequence of length \(t\) of data generated from distribution \(B\).We conjecture that the i.i.d. assumption could be eliminated by defining probability distributions over sequences of arbitrary length, though this complication would not add conceptual clarity. Let \(\mathbf{F}\) be a framework (in this case, a set of probability distributions or densities).Let any \(P(\,)\) functions be either a probability distribution function or probability density function, as appropriate. Let \(M_\mathbf{F}\) be a method that takes a data sequence \(X\) as input and outputs a distribution

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David Danks
University of California, San Diego

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