Anders Bredahl Kock

Statistics and Probability · 2009–2017

A researcher in the Science corpus: 8 papers; trusts 82 researchers and is trusted by 21 researchers here, as inferred from the citation graph.

Subfields

• Statistics and Probability — 90 citations into it; #3,005 of 12,932 by trust here, #3,609 by citations
• Economics and Econometrics — 33 citations into it; #10,541 of 23,481 by trust here, #16,151 by citations
• Artificial Intelligence — 32 citations into it; #30,007 of 35,345 by trust here, #29,412 by citations
• Finance — 22 citations into it
• Statistical Learning Theory — 17 citations into it
• Management Science and Operations Research — 14 citations into it; #11,108 of 11,946 by trust here, #7,638 by citations
• Control and Systems Engineering — 12 citations into it; #4,478 of 8,257 by trust here, #3,516 by citations
• Optimization & Training — 12 citations into it

Whom Anders Bredahl Kock trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Robert Tibshirani
2. Hui Zou
3. Jianqing Fan
4. James H. Stock
5. Alexandre Belloni
6. Sara A. van de Geer
7. Serena Ng
8. E.J. Candes
9. Peter Buhlmann
10. Mark W. Watson

Who trusts Anders Bredahl Kock overall

1. Laurent Callot
2. Ricardo P. Masini
3. Yoshimasa Uematsu
4. Marcelo C. Medeiros
5. David Salinas
6. Martin Brandenburg
7. Timo Teräsvirta
8. Matteo Barigozzi
9. Shinya Tanaka
10. Vira Semenova

Papers from Anders Bredahl Kock's perspective

Ordered by how strongly the researchers Anders Bredahl Kock trusts endorse each paper. Same corpus, a different order for every researcher.

1. Regression Shrinkage and Selection via the Lasso
2. Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
3. The Adaptive Lasso and Its Oracle Properties
4. Asymptotics for lasso-type estimators
5. Model selection and estimation in regression with grouped variables
6. Ideal spatial adaptation by wavelet shrinkage
7. Estimating the Dimension of a Model
8. The Dantzig selector: Statistical estimation when P is much larger than n
9. Sure independence screening for ultrahigh dimensional feature space
10. Addendum: Regularization and variable selection via the elastic net

Their papers

• Asymptotically Honest Confidence Regions for High Dimensional Parameters by the Desparsified Conservative Lasso (2014) — 74 citations
• CONSISTENT AND CONSERVATIVE MODEL SELECTION WITH THE ADAPTIVE LASSO IN STATIONARY AND NONSTATIONARY AUTOREGRESSIONS (2015) — 53 citations
• Oracle Inequalities for High Dimensional Vector Autoregressions (2012) — 247 citations
• Modeling and Forecasting Large Realized Covariance Matrices and Portfolio Choice (2017) — 94 citations
• Oracle Efficient Estimation and Forecasting with the Adaptive Lasso and the Adaptive Group Lasso in Vector Autoregressions (2012) — 31 citations
• Forecasting Macroeconomic Variables Using Neural Network Models and Three Automated Model Selection Techniques (2016) — 46 citations
• Commutative monads as a theory of distributions (2011) — 55 citations
• Synthetic Geometry of Manifolds (2009) — 54 citations