Hierarchical clustering and matrix completion for the reconstruction of world input-output tables

DOI10.1007/s10182-022-00448-6arXiv2203.08819OpenAlexW4281966417MaRDI QIDQ6065677

Francesco Biancalani, Massimo Riccaboni, Rodolfo Metulini, Giorgio Gnecco

Publication date: 15 November 2023

Published in: AStA. Advances in Statistical Analysis (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2203.08819

zbMATH Keywords

matrix completionhierarchical clusteringinput-output tablespanel data analysisLASSO-like nuclear norm penalty

Mathematics Subject Classification ID

Statistics (62-XX)

Cites Work

• Estimating the Number of Clusters in a Data Set Via the Gap Statistic
• Ward's hierarchical agglomerative clustering method: which algorithms implement Ward's criterion?
• A network analysis of the Italian overnight money market
• Silhouettes: a graphical aid to the interpretation and validation of cluster analysis
• Input-output networks offer new insights of economic structure
• Robust linear optimization under matrix completion
• Algorithmic Aspects of Machine Learning
• Updating input–output matrices: assessing alternatives through simulation
• The Power of Convex Relaxation: Near-Optimal Matrix Completion
• Restricted strong convexity and weighted matrix completion: Optimal bounds with noise
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