Latent Dirichlet Allocation Coupled with Time Series Analyses

AICc | Calculate AICc |

autocorr_plot | Produce the autocorrelation panel for the TS diagnostic plot... |

check_changepoints | Check that a set of change point locations is proper |

check_control | Check that a control list is proper |

check_document_covariate_table | Check that the document covariate table is proper |

check_document_term_table | Check that document term table is proper |

check_formula | Check that a formula is proper |

check_formulas | Check that formulas vector is proper and append the response... |

check_LDA_models | Check that LDA model input is proper |

check_nchangepoints | Check that nchangepoints vector is proper |

check_seeds | Check that nseeds value or seeds vector is proper |

check_timename | Check that the time vector is proper |

check_topics | Check that topics vector is proper |

check_weights | Check that weights vector is proper |

count_trips | Count trips of the ptMCMC particles |

diagnose_ptMCMC | Calculate ptMCMC summary diagnostics |

document_weights | Calculate document weights for a corpus |

ecdf_plot | Produce the posterior distribution ECDF panel for the TS... |

est_changepoints | Use ptMCMC to estimate the distribution of change point... |

est_regressors | Estimate the distribution of regressors, unconditional on the... |

expand_TS | Expand the TS models across the factorial combination of LDA... |

iftrue | Replace if TRUE |

jornada | Jornada rodent data |

LDA_msg | Create the model-running-message for an LDA |

LDA_set | Run a set of Latent Dirichlet Allocation models |

LDA_set_control | Create control list for set of LDA models |

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

LDA_TS | Run a full set of Latent Dirichlet Allocations and Time... |

LDA_TS_control | Create the controls list for the LDATS model |

logLik.LDA_VEM | Calculate the log likelihood of a VEM LDA model fit |

logLik.multinom_TS_fit | Log likelihood of a multinomial TS model |

logLik.TS_fit | Determine the log likelihood of a Time Series model |

logsumexp | Calculate the log-sum-exponential (LSE) of a vector |

memoise_fun | Logical control on whether or not to memoise |

messageq | Optionally generate a message based on a logical input |

mirror_vcov | Create a properly symmetric variance covariance matrix |

modalvalue | Determine the mode of a distribution |

multinom_TS | Fit a multinomial change point Time Series model |

multinom_TS_chunk | Fit a multinomial Time Series model chunk |

normalize | Normalize a vector |

package_chunk_fits | Package the output of the chunk-level multinomial models into... |

package_LDA_set | Package the output from LDA_set |

package_LDA_TS | Package the output of LDA_TS |

package_TS | Summarize the Time Series model |

package_TS_on_LDA | Package the output of TS_on_LDA |

plot.LDA_set | Plot a set of LDATS LDA models |

plot.LDA_TS | Plot the key results from a full LDATS analysis |

plot.LDA_VEM | Plot the results of an LDATS LDA model |

plot.TS_fit | Plot an LDATS TS model |

posterior_plot | Produce the posterior distribution histogram panel for the TS... |

prep_chunks | Prepare the time chunk table for a multinomial change point... |

prep_cpts | Initialize and update the change point matrix used in the... |

prep_ids | Initialize and update the chain ids throughout the ptMCMC... |

prep_LDA_control | Set the control inputs to include the seed |

prep_pbar | Initialize and tick through the progress bar |

prep_proposal_dist | Pre-calculate the change point proposal distribution for the... |

prep_ptMCMC_inputs | Prepare the inputs for the ptMCMC algorithm estimation of... |

prep_saves | Prepare and update the data structures to save the ptMCMC... |

prep_temp_sequence | Prepare the ptMCMC temperature sequence |

prep_TS_data | Prepare the model-specific data to be used in the TS analysis... |

print.LDA_TS | Print the selected LDA and TS models of LDA_TS object |

print_model_run_message | Print the message to the console about which combination of... |

print.TS_fit | Print a Time Series model fit |

print.TS_on_LDA | Print a set of Time Series models fit to LDAs |

proposed_step_mods | Fit the chunk-level models to a time series, given a set of... |

rho_lines | Add change point location lines to the time series plot |

rodents | Portal rodent data |

select_LDA | Select the best LDA model(s) for use in time series |

select_TS | Select the best Time Series model |

set_gamma_colors | Prepare the colors to be used in the gamma time series |

set_LDA_plot_colors | Prepare the colors to be used in the LDA plots |

set_LDA_TS_plot_cols | Create the list of colors for the LDATS summary plot |

set_rho_hist_colors | Prepare the colors to be used in the change point histogram |

set_TS_summary_plot_cols | Create the list of colors for the TS summary plot |

sim_LDA_data | Simulate LDA data from an LDA structure given parameters |

sim_LDA_TS_data | Simulate LDA_TS data from LDA and TS model structures and... |

sim_TS_data | Simulate TS data from a TS model structure given parameters |

softmax | Calculate the softmax of a vector or matrix of values |

step_chains | Conduct a within-chain step of the ptMCMC algorithm |

summarize_etas | Summarize the regressor (eta) distributions |

summarize_rhos | Summarize the rho distributions |

swap_chains | Conduct a set of among-chain swaps for the ptMCMC algorithm |

trace_plot | Produce the trace plot panel for the TS diagnostic plot of a... |

TS | Conduct a single multinomial Bayesian Time Series analysis |

TS_control | Create the controls list for the Time Series model |

TS_diagnostics_plot | Plot the diagnostics of the parameters fit in a TS model |

TS_on_LDA | Conduct a set of Time Series analyses on a set of LDA models |

TS_summary_plot | Create the summary plot for a TS fit to an LDA model |

verify_changepoint_locations | Verify the change points of a multinomial time series model |

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.