infer_prior_beliefs: Infer prior beliefs based on adaptation behavior

In kleinschmidt/beliefupdatr: Belief updating for phonetic adaptation

Description

This takes training and test data, the names of the columns, and (optionally) the number of blocks to split the trials into, and stan parameters, and uses stan to draw samples from the prior beliefs that match the behavior.

Usage

infer_prior_beliefs(df, cue, category, response, condition, ranefs,
  n_blocks, test_df = df, ...)

Arguments

df	Data frame with adaptation data
cue	(Quoted) name of columns in training and test which have the cue values.
category	(Quoted) name of column in training data with the correct category labels.
response	(Quoted) name of column in test data with responses
condition	(Quoted) name of column with group identifiers
ranefs	(Quoted) name of column(s) with random effect grouping variables (like subject IDs).
n_blocks	Number of blocks to divide data into.
test_df	(optional) data frame with test data (all data is used as test by default).
...	Additional parameters are passed to sampling

Value

A stanfit object with the fitted stan model.

See Also

extract_prior_samples to get a data frame of samples from the prior belief parameters.

kleinschmidt/beliefupdatr documentation built on May 24, 2020, 8:26 p.m.