Alexander Petersen

Statistics and Probability · 2016–2020

A researcher in the Science corpus: 5 papers; trusts 63 researchers and is trusted by 9 researchers here, as inferred from the citation graph.

Subfields

• Statistics and Probability — 43 citations into it; #4,139 of 12,932 by trust here, #6,552 by citations
• Artificial Intelligence — 30 citations into it; #17,637 of 35,345 by trust here, #29,412 by citations
• Cognitive Neuroscience — 12 citations into it
• Applied Mathematics — 10 citations into it
• Geometry and Topology — 10 citations into it; #4,028 of 7,422 by trust here, #5,008 by citations
• Economics and Econometrics — 9 citations into it; #17,128 of 23,481 by trust here, #20,730 by citations
• Radiology, Nuclear Medicine and Imaging — 8 citations into it
• Environmental Engineering — 7 citations into it

Whom Alexander Petersen trusts overall

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

1. Nicholas John Higham
2. Nicholas I. Fisher
3. Stergios B. Fotopoulos
4. C. M
5. L. K. Ferreira
6. Jianqing Fan
7. Peter Craven
8. H. Qi
9. Alois Kneip
10. H. Muller

Who trusts Alexander Petersen overall

1. Laya Ghodrati
2. H. Muller
3. Paromita Dubey
4. Chao Zhang
5. Kyunghee Han
6. Victor M. Panaretos
7. Piotr Kokoszka
8. Yaqing Chen
9. Xiongtao Dai
10. Zhenhua Lin

Papers from Alexander Petersen's perspective

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

1. High-dimensional graphs and variable selection with the Lasso
2. Linear Processes in Function Spaces: Theory And Applications
3. Regression Shrinkage and Selection via the Lasso
4. Functional Data Analysis for Sparse Longitudinal Data
5. Local polynomial modelling and its applications
6. Inference for Functional Data with Applications
7. Spline Models for Observational Data
8. LARGE SAMPLE THEORY OF INTRINSIC AND EXTRINSIC SAMPLE MEANS ON MANIFOLDS—II
9. Topics in Optimal Transportation
10. Linear Processes in Function Spaces

Their papers

• Functional data analysis for density functions by transformation to a Hilbert space (2016) — 214 citations
• Fréchet regression for random objects with Euclidean predictors (2016) — 256 citations
• Forecasting of density functions with an application to cross-sectional and intraday returns (2019) — 58 citations
• Wasserstein autoregressive models for density time series (2020) — 68 citations
• Partial Separability and Functional Graphical Models for Multivariate Gaussian Processes (2019) — 55 citations