The DOI matches its OpenAlex record; 18 of the 18 references it cites were found in a registry or an index.
The Nonparanormal: Semiparametric Estimation of High Dimensional Undirected Graphs
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Cites
Regression shrinkage and selection via the lasso
Tibshirani, R. (1996) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1996.tb02080.x · Cited by 51,482
Sparse inverse covariance estimation with the graphical lasso
Friedman, J., Hastie, T., & Tibshirani, R. (2008) · Biostatistics · doi:10.1093/biostatistics/kxm045 · Cited by 6,355
Fonctions de répartition à N dimensions et leurs marges
Sklar, M. (1959) · HAL · Cited by 4,671
Hastie, T., & Tibshirani, R. (1986) · Statistical Science · doi:10.1214/ss/1177013604 · Cited by 3,409
High dimensional graphs and variable selection with the Lasso
Meinshausen, N., & Bühlmann, P. (2006) · Cited by 2,539
Weak Convergence and Empirical Processes: With Applications to Statistics
Wellner, J. A. (1996) · Medical Entomology and Zoology · Cited by 1,969
Model selection and estimation in the Gaussian graphical model
Yuan, M., & Lin, Y. (2007) · Biometrika · doi:10.1093/biomet/asm018 · Cited by 1,627
Banerjee, O., Ghaoui, L. E., & d’Aspremont, A. (2007) · arXiv (Cornell University) · doi:10.1145/1390681.1390696 · Cited by 1,233
Sparse Permutation Invariant Covariance Estimation
Rothman, A., Bickel, P. J., Levina, E., & Zhu, J. (2007) · Cited by 686
Ravikumar, P., Lafferty, J., Liu, H., & Wasserman, L. (2009) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.1467-9868.2009.00718.x · Cited by 535
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Cited by
A tutorial on regularized partial correlation networks
Epskamp, S., & Fried, E. I. (2018) · Psychological Methods · doi:10.1037/met0000167 · Cited by 2,918
Sparse and Compositionally Robust Inference of Microbial Ecological Networks
Kurtz, Z. D., Müller, C. L., Miraldi, E. R., Littman, D. R., Blaser, M. J., & Bonneau, R. A. (2015) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1004226 · Cited by 1,799
High-dimensional semiparametric Gaussian copula graphical models
Liu, H., Han, F., Yuan, M., Lafferty, J., & Wasserman, L. (2012) · The Annals of Statistics · doi:10.1214/12-aos1037 · Cited by 507
Self-citationThe huge Package for High-dimensional Undirected Graph Estimation in R
Zhao, T., Liu, H., Roeder, K., Lafferty, J., & Wasserman, L. (2020) · PubMed · doi:10.48550/arxiv.2006.14781 · Cited by 465
Self-citationEstimating psychological networks and their accuracy: A tutorial paper
Epskamp, S., Borsboom, D., & Fried, E. I. (2018) · Behavior Research Methods · doi:10.3758/s13428-017-0862-1 · Cited by 5,715
Metadata
- Authors
- Liu, H., Lafferty, J., & Wasserman, L.
- Published
- 2018-01-01
- Volume
- 10
- Issue
- 80
- Pages
- 2295-2328
- OpenAlex
- W2137892504
- Cited by
- 621
- References
- 18
- FWCI
- 45.55
- Type
- journal article
- Language
- en
- Open access
- green
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- Liu, H., Lafferty, J., & Wasserman, L. (2018). The Nonparanormal: Semiparametric Estimation of High Dimensional Undirected Graphs. https://doi.org/10.1184/r1/6610712.v1
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
