cymr.fit.Recall#

class cymr.fit.Recall#

Base class for evaluating a model of free recall.

studypandas.DataFrame

Study list information.

recallpandas.DataFrame

Recall period information for each list.

paramdict

Model parameter values.

patternsdict

May include keys: ‘vector’ and/or ‘similarity’. Vectors are used to set distributed model representations. Similarity matrices are used to set item connections. Vector and similarity values are dicts of (feature: array) specifying an array for one or more named features, with an [items x units] array for vector representations, or [items x items] for similarity matrices.

__init__()#

Methods

__init__()

fit_indiv(data, param_def[, patterns, ...])

Fit parameters to individual subjects.

fit_subject(subject_data, param_def[, ...])

Fit a model to data for one subject.

generate(data, group_param[, subj_param, ...])

Generate simulated data for all subjects.

generate_subject(study, recall, param[, ...])

Generate simulated data for one subject.

likelihood(data, group_param[, subj_param, ...])

Log likelihood summed over all subjects.

likelihood_subject(study, recall, param[, ...])

Log likelihood of data for one subject based on a given model.

parameter_recovery(data, n_sample, param_def)

Run multiple iterations of parameter recovery.

parameter_sweep(data, group_param, ...[, ...])

Simulate data with varying parameters.

prepare_sim(subject_data[, study_keys, ...])

Prepare data for simulation.

prepare_subject(subject, data, group_param)

Prepare parameters and data for a subject.

record(data, group_param[, subj_param, ...])

Record model states during a simulation.

record_subject(study, recall, param[, ...])

Record model state during simulation of data for one subject.