A discussion of 'Sparse Bayesian factor analysis when the number of factors is unknown' by Sylvia Fruhwirth-Schnatter, Darjus Hosszejni and Hedibert Freitas Lopes
Hauzenberger, Niko and Koop, Gary (2024) A discussion of 'Sparse Bayesian factor analysis when the number of factors is unknown' by Sylvia Fruhwirth-Schnatter, Darjus Hosszejni and Hedibert Freitas Lopes. Bayesian Analysis. ISSN 1936-0975 (In Press) (https://doi.org/10.1214/24-BA1423)
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Abstract
Conditional on knowing the number of factors, r, analysis in static and dynamic factor models is straightforward for the Bayesian. However, inference on r is challenging. A Bayesian could use marginal likelihoods to select the number of factors (see Geweke, 1996). But in the standard big data setups nowadays (which involve a large number of variables/measurements m), this is computationally cumbersome, requiring the estimation of a large set of models that vary in r (≤ m).
ORCID iDs
Hauzenberger, Niko ORCID: https://orcid.org/0000-0002-2683-8421 and Koop, Gary ORCID: https://orcid.org/0000-0002-6091-378X;-
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Item type: Article ID code: 89834 Dates: DateEvent4 July 2024Published4 July 2024AcceptedSubjects: Social Sciences > Economic Theory > Methodology > Mathematical economics. Quantitative methods Department: Strathclyde Business School > Economics Depositing user: Pure Administrator Date deposited: 04 Jul 2024 09:34 Last modified: 02 Oct 2024 13:08 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/89834