Model selection criteria with data dependent penalty, with applications to data-driven neyman smooth tests
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Publication:4512746
DOI10.1080/10485250008832828zbMath1056.62519OpenAlexW2089539734MaRDI QIDQ4512746
Publication date: 2000
Published in: Journal of Nonparametric Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/10485250008832828
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Cites Work
- Unnamed Item
- Quantile estimation with a complex survey design
- Testing goodness-of-fit in regression via order selection criteria
- An \(L_2\) error test with order selection and thresholding
- Appropriate penalties in the final prediction error criterion: A decision theoretic approach
- Nonparametric smoothing and lack-of-fit tests
- Regression and time series model selection in small samples
- On the Distributional Properties of Model Selection Criteria
- Selection of the order of an autoregressive model by Akaike's information criterion
- Data-Driven Version of Neyman's Smooth Test of Fit
- Smoothing-based lack-of-fit tests: variations on a theme
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