LDATS (Q139600)
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Latent Dirichlet Allocation Coupled with Time Series Analyses
| Language | Label | Description | Also known as |
|---|---|---|---|
| English | LDATS |
Latent Dirichlet Allocation Coupled with Time Series Analyses |
Statements
19 September 2023
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Combines Latent Dirichlet Allocation (LDA) and Bayesian multinomial time series methods in a two-stage analysis to quantify dynamics in high-dimensional temporal data. LDA decomposes multivariate data into lower-dimension latent groupings, whose relative proportions are modeled using generalized Bayesian time series models that include abrupt changepoints and smooth dynamics. The methods are described in Blei et al. (2003) <doi:10.1162/jmlr.2003.3.4-5.993>, Western and Kleykamp (2004) <doi:10.1093/pan/mph023>, Venables and Ripley (2002, ISBN-13:978-0387954578), and Christensen et al. (2018) <doi:10.1002/ecy.2373>.
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