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

In weecology/LDATS: Latent Dirichlet Allocation Coupled with Time Series Analyses

Description

Takes the list of fitted chunk-level models returned from TS_chunk_memo (the memoised version of multinom_TS_chunk and packages it as a multinom_TS_fit object. This involves naming the model fits based on the chunk time windows, combining the log likelihood values across the chunks, and setting the class of the output object.

Usage

package_chunk_fits(chunks, fits)

Arguments

chunks	Data frame of start and end times for each chunk (row).
fits	List of chunk-level fits returned by TS_chunk_memo, the memoised version of multinom_TS_chunk.

Value

Object of class multinom_TS_fit, which is a list of [1] chunk-level model fits, [2] the total log likelihood combined across all chunks, and [3] the chunk time data table.

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
  weights <- document_weights(dtt)
  formula <- gamma ~ 1
  changepoints <- c(20,50)
  timename <- "newmoon"
  TS_chunk_memo <- memoise_fun(multinom_TS_chunk, TRUE)
  chunks <- prep_chunks(dct, changepoints, timename)
  nchunks <- nrow(chunks)
  fits <- vector("list", length = nchunks)
  for (i in 1:nchunks){
    fits[[i]] <- TS_chunk_memo(dct, formula, chunks[i, ], timename, 
                               weights, TS_control())
  }
  package_chunk_fits(chunks, fits) 

weecology/LDATS documentation built on March 28, 2020, 11:20 a.m.