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LDATS  

Latent Dirichlet Allocation Coupled with Time Series Analyses
View on CRAN: Click here


Download and install LDATS package within the R console
Install from CRAN:
install.packages("LDATS")

Install from Github:
library("remotes")
install_github("cran/LDATS")

Install by package version:
library("remotes")
install_version("LDATS", "0.3.0")



Attach the package and use:
library("LDATS")
Maintained by
Juniper L. Simonis
[Scholar Profile | Author Map]
First Published: 2019-08-01
Latest Update: 2023-09-19
Description:
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) , Western and Kleykamp (2004) , Venables and Ripley (2002, ISBN-13:978-0387954578), and Christensen et al. (2018) .
How to cite:
Juniper L. Simonis (2019). LDATS: Latent Dirichlet Allocation Coupled with Time Series Analyses. R package version 0.3.0, https://cran.r-project.org/web/packages/LDATS. Accessed 02 May. 2025.
Previous versions and publish date:
0.2.4 (2019-08-01 11:50), 0.2.6 (2020-03-03 10:00), 0.2.7 (2020-03-19 12:10)
Other packages that cited LDATS R package
View LDATS citation profile
Other R packages that LDATS depends, imports, suggests or enhances
Complete documentation for LDATS
Functions, R codes and Examples using the LDATS R package
Some associated functions: AICc . LDATS . LDA_TS . LDA_TS_control . LDA_msg . LDA_set . LDA_set_control . TS . TS_control . TS_diagnostics_plot . TS_on_LDA . TS_summary_plot . autocorr_plot . check_LDA_models . check_changepoints . check_control . check_document_covariate_table . check_document_term_table . check_formula . check_formulas . check_nchangepoints . check_seeds . check_timename . check_topics . check_weights . count_trips . diagnose_ptMCMC . document_weights . ecdf_plot . est_changepoints . est_regressors . expand_TS . iftrue . jornada . logLik.LDA_VEM . logLik.TS_fit . logLik.multinom_TS_fit . logsumexp . memoise_fun . messageq . mirror_vcov . modalvalue . multinom_TS . multinom_TS_chunk . normalize . package_LDA_TS . package_LDA_set . package_TS . package_TS_on_LDA . package_chunk_fits . plot.LDA_TS . plot.LDA_VEM . plot.LDA_set . plot.TS_fit . posterior_plot . prep_LDA_control . prep_TS_data . prep_chunks . prep_cpts . prep_ids . prep_pbar . prep_proposal_dist . prep_ptMCMC_inputs . prep_saves . prep_temp_sequence . print.LDA_TS . print.TS_fit . print.TS_on_LDA . print_model_run_message . proposed_step_mods . rho_lines . rodents . select_LDA . select_TS . set_LDA_TS_plot_cols . set_LDA_plot_colors . set_TS_summary_plot_cols . set_gamma_colors . set_rho_hist_colors . sim_LDA_TS_data . sim_LDA_data . sim_TS_data . softmax . step_chains . summarize_etas . summarize_rhos . swap_chains . trace_plot . verify_changepoint_locations . 
Some associated R codes: LDA.R . LDATS.R . LDA_TS.R . LDA_TS_plots.R . LDA_plots.R . TS.R . TS_on_LDA.R . TS_plots.R . data.R . multinom_TS.R . ptMCMC.R . simulate.R . utilities.R .  Full LDATS package functions and examples
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