• Corpus ID: 238419483

High Dimensional Logistic Regression Under Network Dependence

@inproceedings{Mukherjee2021HighDL,
  title={High Dimensional Logistic Regression Under Network Dependence},
  author={Somabha Mukherjee and Sagnik Halder and Bhaswar B. Bhattacharya and George Michailidis},
  year={2021}
}
Abstract. Logistic regression is one of the most fundamental methods for modeling the probability of a binary outcome based on a collection of covariates. However, the classical formulation of logistic regression relies on the independent sampling assumption, which is often violated when the outcomes interact through an underlying network structure, such as over a temporal/spatial domain or on a social network. This necessitates the development of models that can simultaneously handle both the… 

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