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On Various Confidence Intervals Post-Model-Selection

On Various Confidence Intervals Post-Model-Selection

10 January 2014
Hannes Leeb
B. M. Potscher
K. Ewald
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Papers citing "On Various Confidence Intervals Post-Model-Selection"

12 / 12 papers shown
Title
Black-box Selective Inference via Bootstrapping
Black-box Selective Inference via Bootstrapping
Sifan Liu
Jelena Markovic-Voronov
Jonathan E. Taylor
CML
TPM
19
2
0
28 Mar 2022
Mixture of Linear Models Co-supervised by Deep Neural Networks
Mixture of Linear Models Co-supervised by Deep Neural Networks
Beomseok Seo
Lin Lin
Jia Li
9
6
0
05 Aug 2021
Inference in High-dimensional Linear Regression
Inference in High-dimensional Linear Regression
Heather S. Battey
Nancy Reid
16
4
0
22 Jun 2021
Lasso Inference for High-Dimensional Time Series
Lasso Inference for High-Dimensional Time Series
R. Adámek
Stephan Smeekes
Ines Wilms
AI4TS
26
33
0
21 Jul 2020
Admissibility of the usual confidence set for the mean of a univariate
  or bivariate normal population: The unknown-variance case
Admissibility of the usual confidence set for the mean of a univariate or bivariate normal population: The unknown-variance case
Hannes Leeb
Paul Kabaila
16
4
0
20 Sep 2018
In Defense of the Indefensible: A Very Naive Approach to
  High-Dimensional Inference
In Defense of the Indefensible: A Very Naive Approach to High-Dimensional Inference
Sen Zhao
Daniela Witten
Ali Shojaie
39
57
0
16 May 2017
Uniformly valid confidence intervals post-model-selection
Uniformly valid confidence intervals post-model-selection
F. Bachoc
David Preinerstorfer
Lukas Steinberger
24
48
0
03 Nov 2016
Simultaneous confidence bands for contrasts between several nonlinear
  regression curves
Simultaneous confidence bands for contrasts between several nonlinear regression curves
XiaoPeng Lu
S. Kuriki
8
10
0
17 Oct 2015
Valid confidence intervals for post-model-selection predictors
Valid confidence intervals for post-model-selection predictors
F. Bachoc
Hannes Leeb
B. M. Potscher
31
54
0
15 Dec 2014
Confidence Sets Based on Penalized Maximum Likelihood Estimators in
  Gaussian Regression
Confidence Sets Based on Penalized Maximum Likelihood Estimators in Gaussian Regression
B. M. Potscher
U. Schneider
102
53
0
10 Jun 2008
Evaluation and selection of models for out-of-sample prediction when the
  sample size is small relative to the complexity of the data-generating
  process
Evaluation and selection of models for out-of-sample prediction when the sample size is small relative to the complexity of the data-generating process
Hannes Leeb
76
36
0
22 Feb 2008
Confidence Sets Based on Sparse Estimators Are Necessarily Large
Confidence Sets Based on Sparse Estimators Are Necessarily Large
B. M. Potscher
98
41
0
07 Nov 2007
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