Romeijn, Jan-Willem (2016) Inherent Complexity: a problem for Statistical Model Evaluation. In: UNSPECIFIED.
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Abstract
This paper investigates a problem for statistical model evaluation, in particular for curve fitting: by employing a different family of curves we can fit a scatter plot almost perfectly at apparently minor costs in terms of model complexity. The problem is resolved by an appeal to prior probabilities. This leads to some general lessons about how to approach model evaluation.
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| Item Type: | Conference or Workshop Item (UNSPECIFIED) | ||||||
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| Keywords: | curve fitting, model selection, statistics | ||||||
| Subjects: | General Issues > Confirmation/Induction Specific Sciences > Probability/Statistics |
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| Depositing User: | Dr Jan-Willem Romeijn | ||||||
| Date Deposited: | 31 Oct 2016 12:59 | ||||||
| Last Modified: | 31 Oct 2016 12:59 | ||||||
| Item ID: | 12570 | ||||||
| Subjects: | General Issues > Confirmation/Induction Specific Sciences > Probability/Statistics |
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| Date: | 30 October 2016 | ||||||
| URI: | https://philsci-archive.pitt.edu/id/eprint/12570 |
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