LDATS: Package to conduct two-stage analyses combining Latent...

In LDATS: Latent Dirichlet Allocation Coupled with Time Series Analyses

Package to conduct two-stage analyses combining Latent Dirichlet Allocation with Bayesian Time Series models

Description

Performs two-stage analysis of multivariate temporal data using a combination of Latent Dirichlet Allocation (Blei et al. 2003) and Bayesian Time Series models (Western and Kleykamp 2004) that we extend for multinomial data using softmax regression (Venables and Ripley 2002) following Christensen et al. (2018).

Documentation

Technical mathematical manuscript

End-user-focused vignette worked example

Computational pipeline vignette

Comparison to Christensen et al.

References

Blei, D. M., A. Y. Ng, and M. I. Jordan. 2003. Latent Dirichlet Allocation. Journal of Machine Learning Research 3:993-1022. link.

Christensen, E., D. J. Harris, and S. K. M. Ernest. 2018. Long-term community change through multiple rapid transitions in a desert rodent community. Ecology 99:1523-1529. link.

Venables, W. N. and B. D. Ripley. 2002. Modern and Applied Statistics with S. Fourth Edition. Springer, New York, NY, USA.

Western, B. and M. Kleykamp. 2004. A Bayesian change point model for historical time series analysis. Political Analysis 12:354-374. link.

LDATS documentation built on Sept. 19, 2023, 5:08 p.m.