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.