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On the least-square...
On the least-squares model averaging interval estimator
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- Ankargren, Sebastian (författare)
- Uppsala universitet,Statistiska institutionen
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- Jin, Shaobo, 1987- (författare)
- Uppsala universitet,Statistiska institutionen
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(creator_code:org_t)
- 2017-09-06
- 2018
- Engelska.
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Ingår i: Communications in Statistics - Theory and Methods. - : Informa UK Limited. - 0361-0926 .- 1532-415X. ; 47:1, s. 118-132
- Relaterad länk:
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https://urn.kb.se/re...
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visa fler...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- In many applications of linear regression models, randomness due to model selection is commonly ignored in post-model selection inference. In order to account for the model selection uncertainty, least-squares frequentist model averaging has been proposed recently. We show that the confidence interval from model averaging is asymptotically equivalent to the confidence interval from the full model. The finite-sample confidence intervals based on approximations to the asymptotic distributions are also equivalent if the parameter of interest is a linear function of the regression coefficients. Furthermore, we demonstrate that this equivalence also holds for prediction intervals constructed in the same fashion.
Ämnesord
- NATURVETENSKAP -- Matematik -- Sannolikhetsteori och statistik (hsv//swe)
- NATURAL SCIENCES -- Mathematics -- Probability Theory and Statistics (hsv//eng)
Nyckelord
- Asymptotic equivalence
- Linear model
- Local asymptotics
- Frequentist model averaging
- Post-selection inference
- Statistics
- Statistik
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
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