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Model Selection Principles in Misspecified Models

Model Selection Principles in Misspecified Models

29 May 2010
Jinchi Lv
Jun S. Liu
ArXivPDFHTML

Papers citing "Model Selection Principles in Misspecified Models"

9 / 9 papers shown
Title
A view on model misspecification in uncertainty quantification
A view on model misspecification in uncertainty quantification
Yuko Kato
David Tax
Marco Loog
17
3
0
30 Oct 2022
Bounds in $L^1$ Wasserstein distance on the normal approximation of
  general M-estimators
Bounds in L1L^1L1 Wasserstein distance on the normal approximation of general M-estimators
F. Bachoc
M. Fathi
15
0
0
18 Nov 2021
Efficient and Consistent Data-Driven Model Selection for Time Series
Efficient and Consistent Data-Driven Model Selection for Time Series
Jean‐Marc Bardet
Kamila Kare
William Kengne
12
4
0
19 Oct 2021
Nonasymptotic Laplace approximation under model misspecification
Nonasymptotic Laplace approximation under model misspecification
A. Bhattacharya
D. Pati
11
1
0
16 May 2020
Model-free Feature Screening and FDR Control with Knockoff Features
Model-free Feature Screening and FDR Control with Knockoff Features
Wanjun Liu
Y. Ke
Jingyuan Liu
Runze Li
24
56
0
19 Aug 2019
On the Predictive Risk in Misspecified Quantile Regression
On the Predictive Risk in Misspecified Quantile Regression
Alexander Giessing
Xuming He
37
6
0
02 Feb 2018
Forward-Backward Selection with Early Dropping
Forward-Backward Selection with Early Dropping
Giorgos Borboudakis
Ioannis Tsamardinos
26
95
0
30 May 2017
Schwarz type model comparison for LAQ models
Schwarz type model comparison for LAQ models
Shoichi Eguchi
Hiroki Masuda
16
22
0
06 Jun 2016
Tuning parameter selection in high dimensional penalized likelihood
Tuning parameter selection in high dimensional penalized likelihood
Yingying Fan
C. Tang
21
326
0
11 May 2016
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