Subnetwork estimation for spatial autoregressive models in large-scale networks-Reference-Cited by-同舟云学术

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Subnetwork estimation for spatial autoregressive models in large-scale networks

Published:2023-01-01 Issue:1 Volume:17 Page:
ISSN:1935-7524
Container-title:Electronic Journal of Statistics
language:
Short-container-title:Electron. J. Statist.

Author:

Li Xuetong¹,Wang Feifei²,Lan Wei³,Wang Hansheng¹

Affiliation:

1. Guanghua School of Management, Peking University, Beijing, China

2. Center for Applied Statistics, Renmin University of China, Beijing, China

3. School of Statistics and Center of Statistical Research, Southwestern University of Finance and Economics, Chengdu, China

Publisher

Institute of Mathematical Statistics

Subject

Statistics and Probability,Statistics, Probability and Uncertainty

Reference57 articles.

1. Abbe, E. (2018), “Community detection and stochastic block models: recent developments,” Journal of Machine Learning Research, 18, 1–86.

2. Al Hasan, M. (2016), “Methods and applications of network sampling,” in Optimization challenges in complex, networked and risky systems, INFORMS, pp. 115–139.

3. Anselin, L. and Bera, A. K. (1998), “Spatial dependence in linear regression models with an introduction to spatial econometrics,” Statistics textbooks and monographs, 155, 237–290.

4. Aravindakshan, A., Peters, K., and Naik, P. A. (2012), “Spatiotemporal allocation of advertising budgets,” Journal of Marketing Research, 49, 1–14.

5. Chen, X., Chen, Y., and Xiao, P. (2013), “The Impact of Sampling and Network Topology on the Estimation of Social Intercorrelations,” Journal of Marketing Research, 50, 95–110.

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