compute_ppm_analyses: Compute PPM analyses
In pmcharrison/hvr: Harmonic Viewpoint Regression

Description Usage Arguments Details Value References

This function models discrete viewpoints using the Prediction by Partial Match (PPM) algorithm.

compute_ppm_analyses(
  parent_dir,
  viewpoint_dir = file.path(parent_dir, "0-viewpoints"),
  output_dir = file.path(parent_dir, "1-ppm"),
  stm_opt = stm_options(),
  ltm_opt = ltm_options(),
  seq_test_folds = list(readRDS(file.path(viewpoint_dir, "about.rds"))$seq_test),
  seq_pretrain = readRDS(file.path(viewpoint_dir, "about.rds"))$seq_pretrain,
  viewpoints = readRDS(file.path(viewpoint_dir, "about.rds"))$discrete_viewpoints
)

`parent_dir`	(Character scalar) The parent directory for the output files, shared with functions such as `compute_viewpoints` and `compute_model_matrix`. Ignored if all other directory arguments are manually specified.
`viewpoint_dir`	(Character scalar) The directory for the already-generated output files from `compute_viewpoints`. The default should be correct if the user used the default `dir` argument in `compute_viewpoints`.
`output_dir`	(Character scalar) The output directory for the PPM analyses. Will be created if it doesn't exist already.
`stm_opt`	Options list for the short-term PPM models, as created by the function `stm_options`.
`ltm_opt`	Options list for the long-term PPM models, as created by the function `ltm_options`.
`seq_test_folds`	List of cross-validation folds for the test sequences. Each fold is represented as an integer vector, with the integers indexing the sequences within the corpus (see `compute_viewpoints`). The algorithm iterates over each fold, predicting the sequences within that fold, and training the model using the combination of a) the sequences from the other folds in `seq_test_folds` and b) the sequences identified in `seq_pretrain`. By default, there is just one fold corresponding to the `seq_test` argument of `compute_viewpoints`.
`seq_pretrain`	(Integer vector) Sequences used to pretrain the model (in addition to any cross-validation training specified by `seq_test_folds`), specified as integer indices of the corpus. Defaults to the complement of `seq_test` as specified in `compute_viewpoints`.
`viewpoints`	List of discrete viewpoints to analyse, in the format produced by the `$discrete_viewpoints` slot of the `about.rds` file produced by `compute_viewpoints`. Defaults to the full set of discrete viewpoints as specified in `compute_viewpoints`.

compute_viewpoints should be run first. By default, only sequences in seq_test (see compute_viewpoints) are modelled using PPM. The default PPM implementation corresponds to that described in \insertCitePearce2005;textualhvr.

The primary output is written to disk in the dir directory. The output matrices provide raw probabilities for each event in the chord alphabet.

\insertAllCited

pmcharrison/hvr documentation built on April 14, 2020, 2:47 a.m.