A note on estimating network dependence in a discrete choice model
type: Item
instance of: scholarly article
title: A note on estimating network dependence in a discrete choice model
zbMATH Open document ID: 1461.91240
author: Jing Zhou
author: Da Huang
author: Hansheng Wang
published in: Statistics and Its Interface
publication date: 2018-09-18T00:00:00Z
review text: This paper studies estimating of network dependence in a discrete choice model in the context of a latent spatial auto-regressive model. Network dependence is considered under a principled binary regression method. A pseudo maximum likelihood method is adopted to estimate the spatial auto-correlation of the network. \(n\) nodes are structured into different pairs and each pair contains two nodes \(i\) and \(j\), leading to \(n(n-1)/2\) pairs. Based upon Taylor's expansion, a log likelihood function is approximated for each pair of nodes. Selected pairs for objective functions have been summed assuming certain independence. The consistency of approximated paired maximum likelihood estimator is studied and a numerical simulation for Sina Weibo is presented.
reviewed by: Yilun Shang
Mathematics Subject Classification ID: 91D30
Mathematics Subject Classification ID: 91B06
Mathematics Subject Classification ID: 62P25
zbMATH DE Number: 6938713
zbMATH Keywords: approximated paired maximum likelihood estimation
zbMATH Keywords: discrete choice model
zbMATH Keywords: social network
zbMATH Keywords: spatial auto-correlation
MaRDI profile type: Publication
full work available at URL: sii.2018.v11.n3.a6
OpenAlex ID: W3124903614
Wikidata QID: Q129228937
DOI: 10.4310/SII.2018.V11.N3.A6
description: scientific article; zbMATH DE number 6938713