Fetching the paper…
Reading the bibliography…
We consider the problem of providing valid inference for a selected parameter in a sparse regression setting.
Markovic, J., Taylor, J. and Taylor, J. (2019), Inference after black box selection · 1901
Earlier work this paper cites.
Cox, D. R. (1975), ‘A note on data-splitting for the evaluation of significance levels’, Biometrika
1975
Earlier work this paper cites.
Snee, R. D. (1977), ‘Validation of regression models: methods and examples’, Technometrics
1977
Earlier work this paper cites.
Bhagwat, K. V. and Subramanian, R. (1978), ‘Inequalities between means of positive operators’, Math. Proc. Camb. Philos. Soc
1978
Earlier work this paper cites.
Efron, B., Hastie, T., Johnstone, I. and Tibshirani, R. (2004), ‘Least angle regression’, Ann. Stat
2004
Earlier work this paper cites.
Rubin, D., Dudoit, S. and van der Laan, M. (2006), ‘A method to increase the power of multiple testing procedures though sample splitting’, Stat. Appl. Genet. Mol. Biol
2006
Earlier work this paper cites.
Kivaranovic, D. and Leeb, H. (2021 b · 2007
Earlier work this paper cites.
Wasserman, L. and Roeder, K. (2009), ‘High-dimensional variable selection’, Ann. Stat
2009
Earlier work this paper cites.
Meinshausen, N. and Bühlmann, P. (2010), ‘Stability selection’, J. R. Statist. Soc. B
2010
Earlier work this paper cites.
Reitermanová, Z. (2010), ‘Data splitting’, WDS’10 Proceedings of Contributed Papers
2010
Earlier work this paper cites.
Zrnic, T. and Jordan, M. I. (2020), Post-selection inference via algorithmic stability · 2011
Earlier work this paper cites.
Fan, J., , Guo, S. and Hao, N. (2012), ‘Variance estimation using refitted cross-validation in ultrahigh dimensional regression’, J. R. Statist. Soc. B
2012
Earlier work this paper cites.
Bayati, M., Erdogdu, M. A. and Montanari, A. (2013), Estimating LASSO risk and noise level’, in
2013
Earlier work this paper cites.
Berk, R., Brown, L., Buja, A., Zhang, K. and Zhao, L. (2013), ‘Valid post-selection inference’, Ann. Stat
2013
Cited alongside, same era.
Shah, R. and Samworth, R. (2013), ‘Variable selection with error control: another look at stability selection’, J. R. Statist. Soc. B
2013
Cited alongside, same era.
Lee, J. D. and Taylor, J. E. (2014), ‘Exact post model selection inference for marginal screening’, Adv. Neural Inf. Process Syst
2014
Cited alongside, same era.
Lockhart, R., Taylor, J. E., Tibshirani, R. and Tibshirani, R. (2014), ‘A significance test for the lasso’, Ann. Stat
2014
Cited alongside, same era.
Loftus, J. R. and Taylor, J. E. (2014), ‘A significance test for forward stepwise model selection’ · 2014
Cited alongside, same era.
Hong, L., Kuffner, T. A. and Martin, R. (2018), ‘On overfitting and post-selection uncertainty assessments’, Biometrika
2018
Later among the works it cites.
Tian, X. and Taylor, J. E. (2018), ‘Selective inference with a randomized response’, Ann. Stat
2018
Later among the works it cites.
Tibshirani, R., Rinaldo, A., Tibshirani, R. and Wasserman, L. (2018), ‘Uniform asymptotic inference and the bootstrap after model selection’, Ann. Stat
2018
Later among the works it cites.
Raic, M. (2019), ‘A multivariate Berry–Esseen theorem with explicit constants’, Bernoulli
2019
Later among the works it cites.
Rinaldo, A., Wasserman, L. and G’Sell, M. (2019), ‘Bootstrapping and sample splitting for high-dimensional, assumption-lean inference’, Ann. Stat
2019
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Ignatiadis, N., Klaus, B., Zaugg, J. and Huber, W. (2016), ‘Data-driven hypothesis weighting increases detection power in genome-scale multiple testing’, Nat. Methods
2016
Cited alongside, same era.
Lee, J. D., Sun, D. L., Sun, Y. and Taylor, J. E. (2016), ‘Exact post-selection inference, with application to the lasso’, Ann. Stat
2016
Cited alongside, same era.
Reid, S., Tibshirani, R. and Friedman, J. (2016), ‘A study of error variance estimation in lasso regression’, Stat. Sin
2016
Cited alongside, same era.
Bachoc, F., Leeb, H. and Pötscher, B. M. (2017), Valid confidence intervals for post-model-selection predictors · 2017
Cited alongside, same era.
Fithian, W., Sun, D. L. and Taylor, J. E. (2017), ‘Optimal inference after model selection’ · 2017
Cited alongside, same era.
R package version 0.6-3. https://CRAN.R-project.org/package=stabs
Hofner, B. and Hothorn, T. (2017), Stability selection with error control · 2017
Cited alongside, same era.
Candès, E., Fan, Y., Janson, L. and Lv, J. (2018), ‘Panning for gold: ‘model‐X’ knockoffs for high dimensional controlled variable selection’, J. R. Statist. Soc. B
2018
Cited alongside, same era.
R package version 1.2.5. https://CRAN.R-project.org/package=selectiveInference
Tibshirani, R., Tibshirani, R., Taylor, J., Loftus, J., Reid, S. and Markovic, J. (2019), selectiveInference: Tools for post-selection inference · 2019
Later among the works it cites.
Bachoc, F., Preinerstorfer, D. and Steinberger, L. (2020), ‘Uniformly valid confidence intervals post-model-selection’, Ann. Stat
2020
Later among the works it cites.
R package version 0.3.3. https://CRAN.R-project.org/package=knockoff
Barber, R. F., Candès, E., Janson, L., Patterson, E. and Sesia, M. (2020), The knockoff filter for controlled variable selection · 2020
Later among the works it cites.
DiCiccio, C. J., DiCiccio, T. J. and Romano, J. P. (2020), ‘Exact tests via multiple data splitting’, Stat. Probab. Lett
2020
Later among the works it cites.
Panigrahi, S., Taylor, J. and Weinstein, A. (2020), ‘Integrative methods for post-selection inference under convex constraints’ · 2020
Later among the works it cites.
Kivaranovic, D. and Leeb, H. (2021 a
2021
Closest in time.
Barber, R. F. and Candès, E. (2015), ‘Controlling the false discovery rate via knockoffs’, Ann. Stat
2085
Closest in time.