Run and Optimize Cross-Situational Word Learning Models

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Documentation for package ‘XSLmodels’ version 0.4.0

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

baseline	Baseline model
bayesian_decay	Bayesian decay model
benitez2020	Benitez et al. (2020) temporal-structure-of-naming experiment data
create_cooc_matrix	Creates co-occurrence matrix from training trials
cross_validated_group_fits	Perform Cross-Validation on Group Fits of a Model
decay	Decay model
fazly	Fazly et al. 2010 probablistic associative model
fgt2009	Frank, Goodman & Tenenbaum (2009) intentional Bayesian word-learning model
fgt2009_rsa	Frank, Goodman & Tenenbaum word-learning model with pragmatic (RSA) reasoning
fgt2009_sweep_alpha	Sweep the lexicon-size prior alpha for an FGT model
fm_corpus	Frank, Tenenbaum & Fernald naturalistic word-learning corpus
gangwani2011_category	Gangwani, Kachergis & Yu simultaneous category + object name learning
get_crossvalidated_model_fit	Get cross-validated model fit
get_example_ambiguous_condition	Get example ambiguous condition
get_example_unambiguous_condition	Get example unambiguous condition
get_fscore	Calculate F-score, precision, recall, and specificity for a knowledge matrix at a given threshold
get_group_model_fit	Get group model fit for a specific model
get_perf	Calculate Luce choice (proportion correct) for each item in a model knowledge matrix
get_roc	Calculate receiver operating characteristic (ROC) scores for a model association Matrix
get_roc_max	Calculate receiver operating characteristic (ROC) scores for a model association Matrix
get_tp	Get true positives (TP), given a knowledge matrix and a gold-standard lexicon
get_train_test_split	Split Data into Training and Testing Sets Based on Indices
guess_and_test	Guess and test model
kachergis2012_highlighting	Kachergis (2012) highlighting experiment data
kachergis_initial_accuracy	Kachergis, Grimmick, & Gureckis initial accuracy experiment data
kalman_filter	Kalman filter associative model
mafc_test	Evaluate m-alternative forced choice test
minerva2	MINERVA2 episodic memory model
multi_sampling	Multi-sampling associative model
new_xslControl	xslControl S3 class
new_xslData	xslData S3 class
new_xslFit	Constructor for xsl_model S3 class
new_xslMod	Constructor for xsl_model S3 class
plot_roc	Calculate receiver operating characteristic (ROC) scores for a model association Matrix
plot_training_trials	Create Animated Plot of Co-Occurrence Matrix from Training Trials
predict_referent	Predict referent selection for a single trial from an association matrix
propose_but_verify	Trueswell et al. 2013 propose-but-verify model
pursuit	Stevens et al. 2014 pursuit model
rem	REM (Retrieving Effectively from Memory) model
rescorla_wagner	Rescorla-Wagner (1972) error-driven associative model
rollins_corpus	CHILDES/Rollins naturalistic word-learning corpus (Frank et al. 2009)
rsa_listener	Rational Speech Act pragmatic listener and speaker
rsa_speaker	Rational Speech Act pragmatic listener and speaker
show_datasets	Show available datasets in the package
show_models	Show available models in the package
softmax_rl	Softmax reinforcement learning model
tilles	Tilles and Fontanari (2013) reinforcement model
todam	TODAM holographic reduced representation model
uncfam	Kachergis 2012
uncfam_attention	Biased associative model with attention scaled to trial uncertainty
uncfam_elimination	Biased associative model with learning by elimination
uncfam_gamma	Kachergis 2012 with a free familiarity exponent
uncfam_predictive	Predictive biased associative model (item-level prediction error)
uncfam_sampling	Kachergis 2012
update_params	Update parameters of xslMod
vlach_debrock2017	Vlach & DeBrock (2017) spaced/massed repetition experiment data
xslControl	xslControl S3 class
xslControl-class	xslControl S3 class
xslData	xslData S3 class
xslData-class	xslData S3 class
xslFit	xslFit S3 class
xslFit-class	xslFit S3 class
xslMod	Constructor for xsl_model S3 class
xslMod-class	Constructor for xsl_model S3 class
xsl_datasets	Cross-situational word learning experiment data
xsl_fit	Fit XSL model using differential evolution
xsl_holdout_datasets	Registry of datasets held out from xsl_datasets
xsl_run	Run XSL model