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  "Title": "Generalized Linear Regression Models on Network-Linked Data with\nStatistical Inference",
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  "Authors@R": "c(person(\"Jianxiang Wang\", email = \"jw1881@scarletmail.rutgers.edu\", role = c(\"aut\", \"cre\")), person(\"Tianxi Li\", email = \"tianxili@umn.edu\", role = c(\"aut\")),\nperson(\"Can M. Le\", email = \"canle@ucdavis.edu\", role = c(\"aut\")))",
  "Description": "Linear regression model and generalized linear models with\nnonparametric network effects on network-linked observations.\nThe model is originally proposed by Le and Li (2022)\n<doi:10.48550/arXiv.2007.00803> and is assumed on observations\nthat are connected by a network or similar relational data\nstructure. A more recent work by Wang, Le and Li (2024)\n<doi:10.48550/arXiv.2410.01163> further extends the framework\nto generalized linear models. All these models are implemented\nin the current package. The model does not assume that the\nrelational data or network structure to be precisely observed;\nthus, the method is provably robust to a certain level of\nperturbation of the network structure. The package contains the\nestimation and inference function for the model.",
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  "Author": "Jianxiang Wang [aut, cre], Tianxi Li [aut], Can M. Le [aut]",
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