Adaptive estimation in structured factor models with applications to overlapping clustering

DOI10.1214/19-AOS1877zbMath1455.62116arXiv1704.06977OpenAlexW3049025113MaRDI QIDQ2215724

Florentina Bunea, Yang Ning, Xin Bing, Marten H. Wegkamp

Publication date: 14 December 2020

Published in: The Annals of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1704.06977

zbMATH Keywords

identificationadaptive estimationminimax estimationmatrix factorizationsupport recoveryoverlapping clusteringhigh-dimensional estimationlatent modelpure variablesgroup recoverysparse loading matrix

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Classification and discrimination; cluster analysis (statistical aspects) (62H30)

Related Items

Inference in latent factor regression with clusterable features, Unnamed Item, Model assisted variable clustering: minimax-optimal recovery and algorithms, A Joint MLE Approach to Large-Scale Structured Latent Attribute Analysis, Optimal discriminant analysis in high-dimensional latent factor models, Detecting approximate replicate components of a high-dimensional random vector with latent structure, A Doubly Enhanced EM Algorithm for Model-Based Tensor Clustering, Statistical inference for structured high-dimensional models. Abstracts from the workshop held March 11--17, 2018, A note on identifiability conditions in confirmatory factor analysis, Nonsparse Learning with Latent Variables, Structured Latent Factor Analysis for Large-scale Data: Identifiability, Estimability, and Their Implications, Unnamed Item, Unnamed Item

Uses Software

• glasso

Cites Work

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