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- W3213778921 abstract "In a two-mode network, the nodes are divided into two types (primary nodes and secondary nodes), and connections exist only between nodes of different types. In reality, in such a twomode network, one-mode network connections may also exist among the primary nodes, and these two kinds of networks are usually not independent and coexistent. In this paper, we first propose a group Rasch mixture network model that focuses on the connections between the primary nodes and the secondary nodes, while simultaneously incorporating the group structure and linkage information of the primary nodes. We then develop a modified expectation–maximization algorithm to estimate the proposed model with a λ-BIC method for selecting the tuning parameter. Additionally, we provide a likelihood ratio test statistic to examine whether the two kinds of networks are independent, and implement the leave-one-out method to construct a network prediction rule. Finally, we establish asymptotic results and demonstrate the numerical performance of the proposed methods using both simulations and the Last.fm dataset." @default.
- W3213778921 created "2021-11-22" @default.
- W3213778921 creator A5051669402 @default.
- W3213778921 creator A5087651522 @default.
- W3213778921 date "2022-03-25" @default.
- W3213778921 modified "2023-09-23" @default.
- W3213778921 title "Statistical inference on group Rasch mixture network models" @default.
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- W3213778921 doi "https://doi.org/10.1002/sta4.436" @default.
- W3213778921 hasPublicationYear "2022" @default.
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