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

In LDATS: Latent Dirichlet Allocation Coupled with Time Series Analyses

Prepare the time chunk table for a multinomial change point Time Series model

Description

Creates the table containing the start and end times for each chunk within a time series, based on the change points (used to break up the time series) and the range of the time series. If there are no change points (i.e. changepoints is NULL, there is still a single chunk defined by the start and end of the time series.

Usage

prep_chunks(data, changepoints = NULL, timename = "time")

Arguments

data	Class data.frame object including the predictor and response variables, but specifically here containing the column indicated by the timename input.
changepoints	Numeric vector indicating locations of the change points. Must be conformable to integer values.
timename	character element indicating the time variable used in the time series. Defaults to "time". The variable must be integer-conformable or a Date. If the variable named is a Date, the input is converted to an integer, resulting in the timestep being 1 day, which is often not desired behavior.

Value

data.frame of start and end times (columns) for each chunk (rows).

Examples

  data(rodents)
  dtt <- rodents$document_term_table
  lda <- LDA_set(dtt, 2, 1, list(quiet = TRUE))
  dct <- rodents$document_covariate_table
  dct$gamma <- lda[[1]]@gamma
  chunks <- prep_chunks(dct, changepoints = 100, timename = "newmoon")   

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