On the role of latent variable models in the era of big data

Francesco Bartolucci, Silvia Bacci and Antonietta Mira

Statistics & Probability Letters, 2018, vol. 136, issue C, 165-169

Abstract: We discuss how latent variable models are useful to deal with the complexities of big data from different perspectives: simplification of data structure; flexible representation of dependence between variables; reduction of selection bias. Problems involved in parameter estimation are also discussed.

Keywords: Bayesian inference; Complex data; Maximum likelihood estimation; Parallel computing; Selection bias (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (1)

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DOI: 10.1016/j.spl.2018.02.023

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