Generalized \(k\)-means in GLMs with applications to the outbreak of COVID-19 in the United States

DOI10.1016/j.csda.2021.107217OpenAlexW3134747312MaRDI QIDQ830116

Ge Lin, Tonglin Zhang

Publication date: 7 May 2021

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2008.03838

zbMATH Keywords

clusteringgeneralized linear models (GLMs)exponential family distributionsCOVID-19generalized \(k\)-meansgeneralized information criterion (GIC)

Mathematics Subject Classification ID

Statistics (62-XX)

Uses Software

• k-means++
• clusterpath

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Estimating the Number of Clusters in a Data Set Via the Gap Statistic
• Algorithm AS 136: A K-Means Clustering Algorithm
• Clustering to minimize the maximum intercluster distance
• Fuzzy clustering algorithms based on the maximum likelihood principle
• Consistency of AIC and BIC in estimating the number of significant components in high-dimensional principal component analysis
• Quasi-likelihood functions
• A constant-factor approximation algorithm for the \(k\)-median problem
• Higher criticism for detecting sparse heterogeneous mixtures.
• Numerical studies of MacQueen's \(k\)-means algorithm for computing the centroidal Voronoi tessellations
• Consistent selection of the number of clusters via crossvalidation
• Asymptotic Statistics
• Model-Based Clustering, Discriminant Analysis, and Density Estimation
• Variance Estimation Using Refitted Cross-Validation in Ultrahigh Dimensional Regression
• Least squares quantization in PCM
• A Bayesian criterion for cluster stability
• Effective containment explains subexponential growth in recent confirmed COVID-19 cases in China
• Regularization Parameter Selections via Generalized Information Criterion
• The Clustering of Regression Models Method with Applications in Gene Expression Data