On the choice of a discrepancy functional for model selection
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Publication:4337107
DOI10.1080/03610929508831654zbMath0875.62201OpenAlexW1979984167MaRDI QIDQ4337107
Michael W. Trosset, Barbara N. Sands
Publication date: 10 November 1997
Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/03610929508831654
robustnessmodel selectionminimum distance estimationdiscrepancy functionalprinciple of parsimonymodel discrimination
Cites Work
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- Likelihood Ratio Tests for Model Selection and Non-Nested Hypotheses
- Nonmetric individual differences multidimensional scaling: An alternating least squares method with optimal scaling features
- Asymptotic methods in statistical decision theory
- Stochastic estimation and testing
- On Kullback-Leibler loss and density estimation
- Minimum Hellinger distance estimates for parametric models
- Pathologies of some minimum distance estimators
- The ``automatic robustness of minimum distance functionals
- Consistent cross-validated density estimation
- Probabilities of Hypotheses and Information-Statistics in Sampling from Exponential-Class Populations
- On the General Problem of Model Selection
- Testing Non-Nested Nonlinear Regression Models
- Information Criteria for Discriminating Among Alternative Regression Models
- On Information and Sufficiency
- An invariant form for the prior probability in estimation problems
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