Frontiers in Latent Variable Analysis

  • J. Christopher Westland
Part of the Studies in Systems, Decision and Control book series (SSDC, volume 22)


Advances in computing have made possible new latent variable methods that were not possible even 5 years ago. Network analysis and machine learning offer some of the most compelling computationally intensive approaches to data analysis. They have achieved objectives—playing chess and go, face and voice recognition, intelligent response to queries, and more—that statisticians might only have dreamt of 20 years ago. One surprising consequence of this intense investment in computationally intensive data analytics has been the surprise appearance of latent constructs that researchers had not hypothesized in advance. These emergent properties represent a whole new landscape for inquiry, theory-building, and latent variable analysis.


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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Information & Decision SystemsUniversity of Illinois at ChicagoChicagoUSA

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