Tom Boot

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All published works

Action	Title	Year	Authors
+ PDF Chat	Uniform inference in linear error-in-variables models: Divide-and-conquer	2024	Tom Boot Artūras Juodis
+ PDF Chat	Inference on LATEs with covariates	2024	Tom Boot Didier Nibbering
+ PDF Chat	Unbiased estimation of the OLS covariance matrix when the errors are clustered	2023	Tom Boot Gianmaria Niccodemi Tom Wansbeek
+	Unbiased estimation of the OLS covariance matrix when the errors are clustered	2023	Tom Boot Gianmaria Niccodemi Tom Wansbeek
+	Joint inference based on Stein-type averaging estimators in the linear regression model	2023	Tom Boot
+	Uniform Inference in Linear Error-in-Variables Models: Divide-and-Conquer	2023	Tom Boot Artūras Juodis
+	Identification- and many instrument-robust inference via invariant moment conditions	2023	Tom Boot Johannes W. Ligtenberg
+	Unbiased estimation of the OLS covariance matrix when the errors are clustered	2022	Tom Boot Gianmaria Niccodemi Tom Wansbeek
+ PDF Chat	Wang and Leng (2016), High-Dimensional Ordinary Least-Squares Projection for Screening Variables, Journal of The Royal Statistical Society Series B, 78, 589–611	2021	Xiangyu Wang Chenlei Leng Tom Boot
+ PDF Chat	Subspace Methods	2019	Tom Boot Didier Nibbering
+ PDF Chat	Forecasting using random subspace methods	2019	Tom Boot Didier Nibbering
+	Confidence Regions for Averaging Estimators	2019	Tom Boot
+	Inference in high-dimensional linear regression models	2017	Tom Boot Didier Nibbering
+	Confidence Intervals in High-Dimensional Regression Based on Regularized Pseudoinverses	2017	Tom Boot Didier Nibbering
+	Scalable simultaneous inference in high-dimensional linear regression models.	2017	Tom Boot Didier Nibbering
+ PDF Chat	Confidence Intervals in High-Dimensional Regression Based on Regularized Pseudoinverses	2017	Tom Boot Didier Nibbering
+	Inference in high-dimensional linear regression models	2017	Tom Boot Didier Nibbering
+	Scalable simultaneous inference in high-dimensional linear regression models	2017	Tom Boot Didier Nibbering
+	Forecasting using Random Subspace Methods	2016	Tom Boot Didier Nibbering
+ PDF Chat	Forecasting Using Random Subspace Methods	2016	Tom Boot Didier Nibbering

Common Coauthors

Coauthor	Papers Together
Didier Nibbering	11
Gianmaria Niccodemi	3
Tom Wansbeek	3
Artūras Juodis	2
Chenlei Leng	1
Johannes W. Ligtenberg	1
Xiangyu Wang	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+	Regression Shrinkage and Selection Via the Lasso	1996	Robert Tibshirani	6
+ PDF Chat	Scaled sparse linear regression	2012	Tao Sun C.-H. Zhang	3
+	Extensions of Lipschitz mappings into a Hilbert space	1984	William B. Johnson Joram Lindenstrauss	3
+	Ridge Regression: Biased Estimation for Nonorthogonal Problems	1970	Arthur E. Hoerl Robert W. Kennard	3
+	Compressed Least-Squares Regression	2009	Odalric Maillard Rémi Munos	3
+	Confidence intervals and hypothesis testing for high-dimensional regression	2014	Adel Javanmard Andrea Montanari	3
+ PDF Chat	Bayesian Compressed Regression	2014	Rajarshi Guhaniyogi David B. Dunson	3
+ PDF Chat	CUR matrix decompositions for improved data analysis	2009	Michael W. Mahoney Petros Drineas	3
+ PDF Chat	Confidence Intervals for Diffusion Index Forecasts and Inference for Factor-Augmented Regressions	2006	Jushan Bai Serena Ng	3
+ PDF Chat	Random Projections for Large-Scale Regression	2017	Gian-Andrea Thanei Christina Heinze Nicolai Meinshausen	3
+ PDF Chat	A study of error variance estimation in Lasso regression	2015	Stephen Reid Robert Tibshirani Jerome H. Friedman	3
+ PDF Chat	Sure Independence Screening for Ultrahigh Dimensional Feature Space	2008	Jianqing Fan Jinchi Lv	3
+ PDF Chat	Complete subset regressions	2013	Graham Elliott Antonio Gargano Allan Timmermann	3
+	Fast monte-carlo algorithms for finding low-rank approximations	2004	Alan Frieze Ravi Kannan Santosh Vempala	3
+	Complete subset regressions with large-dimensional sets of predictors	2015	Graham Elliott Antonio Gargano Allan Timmermann	3
+	Leave‐Out Estimation of Variance Components	2020	Patrick Kline Raffaele Saggio Mikkel Sølvsten	3
+	The matrix angular central Gaussian distribution	1990	Yasuko Chikuse	3
+ PDF Chat	Sampling‐Based versus Design‐Based Uncertainty in Regression Analysis	2020	Alberto Abadie Susan Athey Guido W. Imbens Jeffrey M. Wooldridge	2
+ PDF Chat	Asymptotic theory and wild bootstrap inference with clustered errors	2019	Antoine Djogbenou James G. MacKinnon Morten Ørregaard Nielsen	2
+ PDF Chat	Introduction to the non-asymptotic analysis of random matrices	2012	Roman Vershynin	2
+ PDF Chat	Estimating the error variance in a high-dimensional linear model	2019	Guo Yu Jacob Bien	2
+ PDF Chat	High Dimensional Ordinary Least Squares Projection for Screening Variables	2015	Xiangyu Wang Chenlei Leng	2
+ PDF Chat	Limit expressions for the risk of james‐stein estimators	1982	George Casella Jiunn Tzon Hwang	2
+	A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity	1980	Halbert White	2
+ PDF Chat	Inference with Few Heterogeneous Clusters	2015	Rustam Ibragimov Ulrich K. Müller	2
+	The wild bootstrap for few (treated) clusters	2017	James G. MacKinnon Matthew D. Webb	2
+ PDF Chat	Robust Standard Errors in Small Samples: Some Practical Advice	2016	Guido W. Imbens Michal Kolesár	2
+ PDF Chat	Asymptotic theory for clustered samples	2019	Bruce E. Hansen Seojeong Lee	2
+ PDF Chat	Debiasing the lasso: Optimal sample size for Gaussian designs	2018	Adel Javanmard Andrea Montanari	2
+ PDF Chat	Gene hunting with hidden Markov model knockoffs	2018	Matteo Sesia Chiara Sabatti Emmanuel J. Candès	2
+	High-Dimensional Probability: An Introduction with Applications in Data Science	2018	Roman Vershynin	2
+ PDF Chat	How Much Should We Trust Differences-In-Differences Estimates?	2004	Bertrand Moine Esther Duflo Sendhil Mullainathan	2
+ PDF Chat	Efficient shrinkage in parametric models	2015	Bruce E. Hansen	2
+	Inference with Difference-in-Differences and Other Panel Data	2007	Stephen G. Donald Kevin Lang	2
+ PDF Chat	Frequentist Model Average Estimators	2003	Nils Lid Hjort Gerda Claeskens	2
+	Longitudinal data analysis using generalized linear models	1986	Kung‐Yee Liang Scott L. Zeger	2
+ PDF Chat	Variable Selection in Predictive Regressions	2013	Serena Ng	2
+	The Lagrange Multiplier Test and its Applications to Model Specification in Econometrics	1980	Trevor Breusch A. R. Pagan	2
+ PDF Chat	Revisiting useful approaches to data-rich macroeconomic forecasting	2016	Jan J. J. Groen George Kapetanios	2
+ PDF Chat	Least angle regression	2004	Bradley Efron Trevor Hastie Iain M. Johnstone Robert Tibshirani	2
+ PDF Chat	Some heteroskedasticity-consistent covariance matrix estimators with improved finite sample properties	1985	James G. MacKinnon Halbert White	2
+	Valid post-selection and post-regularization inference: An elementary, general approach	2016	Victor Chernozhukov Martin Spindler Christian Hansen	2
+ PDF Chat	Strong converse for identification via quantum channels	2002	Rudolf Ahlswede Andreas Winter	2
+ PDF Chat	Model Selection and Model Averaging	2009	Cedric E. Ginestet	2
+ PDF Chat	Least Squares Model Averaging	2007	Bruce E. Hansen	2
+	Averaging estimators for autoregressions with a near unit root	2010	Bruce E. Hansen	2
+ PDF Chat	Jackknife model averaging	2011	Bruce E. Hansen Jeffrey S. Racine	2
+ PDF Chat	Estimation of the Mean of a Multivariate Normal Distribution	1981	Charles Stein	2
+	A Statistical Perspective on Algorithmic Leveraging	2014	Ping Ma Michael W. Mahoney Bin Yu	2
+ PDF Chat	A Practitioner’s Guide to Cluster-Robust Inference	2015	A. Colin Cameron Douglas L. Miller	2