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Journal of the American Statistical Association Volume 118, 2023 - Issue 541
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Theory and Methods

Efficient Estimation for Random Dot Product Graphs via a One-Step Procedure

Fangzheng Xiea Department of Statistics, Indiana University, Bloomington, IN;;b Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, MD;View further author information
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Yanxun Xub Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, MD;Correspondence[email protected]
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Pages 651-664 | Received 09 Oct 2019, Accepted 21 Jun 2021, Published online: 04 Aug 2021

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Anirban Mitra, Konasale Prasad & Joshua Cape. On inference for modularity statistics in structured networks. Journal of Computational and Graphical Statistics 0:0, pages 1-26.
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Articles from other publishers (5)

Fangzheng Xie. (2024) Entrywise limit theorems for eigenvectors of signal-plus-noise matrix models with weak signals. Bernoulli 30:1.
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Marcelo Fiori, Bernardo Marenco, Federico Larroca, Paola Bermolen & Gonzalo Mateos. (2024) Gradient-Based Spectral Embeddings of Random Dot Product Graphs. IEEE Transactions on Signal and Information Processing over Networks 10, pages 1-16.
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Xinjie Du & Minh Tang. (2023) Hypothesis testing for equality of latent positions in random graphs. Bernoulli 29:4.
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Fangzheng Xie & Dingbo Wu. (2023) An eigenvector-assisted estimation framework for signal-plus-noise matrix models. Biometrika.
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Joshua Agterberg, Zachary Lubberts & Carey E. Priebe. (2022) Entrywise Estimation of Singular Vectors of Low-Rank Matrices With Heteroskedasticity and Dependence. IEEE Transactions on Information Theory 68:7, pages 4618-4650.
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