A Bayesian latent variable approach to functional principal components analysis with binary and count data
Angelika Linde ()
AStA Advances in Statistical Analysis, 2009, vol. 93, issue 3, 307-333
Keywords: Probabilistic PCA; Logistic PCA; Factor analysis; Exponential family; Variational algorithm; Working observations; Splines (search for similar items in EconPapers)
Date: 2009
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)
Downloads: (external link)
http://hdl.handle.net/10.1007/s10182-009-0113-6 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:alstar:v:93:y:2009:i:3:p:307-333
Ordering information: This journal article can be ordered from
http://www.springer. ... cs/journal/10182/PS2
DOI: 10.1007/s10182-009-0113-6
Access Statistics for this article
AStA Advances in Statistical Analysis is currently edited by Göran Kauermann and Yarema Okhrin
More articles in AStA Advances in Statistical Analysis from Springer, German Statistical Society
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().