A B C D E F G H I L M O P Q R S T U V W
| Agent | Agent |
| agent | Agent |
| arms | Plot |
| average | Plot |
| Bandit | Bandit: Superclass |
| bandit | Bandit: Superclass |
| BasicBernoulliBandit | Bandit: BasicBernoulliBandit |
| BasicGaussianBandit | Bandit: BasicGaussianBandit |
| BootstrapTSPolicy | Policy: Thompson sampling with the online bootstrap |
| check_history_data | Plot |
| clear_data_table | History |
| clipr | Clip vectors |
| ContextualBernoulliBandit | Bandit: Naive Contextual Bernouilli Bandit |
| ContextualBinaryBandit | Bandit: ContextualBinaryBandit |
| ContextualEpochGreedyPolicy | Policy: A Time and Space Efficient Algorithm for Contextual Linear Bandits |
| ContextualEpsilonGreedyPolicy | Policy: ContextualEpsilonGreedyPolicy with unique linear models |
| ContextualHybridBandit | Bandit: ContextualHybridBandit |
| ContextualLinearBandit | Bandit: ContextualLinearBandit |
| ContextualLinTSPolicy | Policy: Linear Thompson Sampling with unique linear models |
| ContextualLogitBandit | Bandit: ContextualLogitBandit |
| ContextualLogitBTSPolicy | Policy: ContextualLogitBTSPolicy |
| ContextualPrecachingBandit | Bandit: ContextualPrecachingBandit |
| ContextualTSProbitPolicy | Policy: ContextualTSProbitPolicy |
| ContextualWheelBandit | Bandit: ContextualWheelBandit |
| ContinuumBandit | Bandit: ContinuumBandit |
| cumulative | History |
| data_table_factors_to_numeric | Convert all factor columns in data.table to numeric |
| dec<- | Decrement |
| dinvgamma | The Inverse Gamma Distribution |
| do_plot | Plot |
| do_step | Agent |
| EpsilonFirstPolicy | Policy: Epsilon First |
| EpsilonGreedyPolicy | Policy: Epsilon Greedy |
| Exp3Policy | Policy: Exp3 |
| FixedPolicy | Policy: Fixed Arm |
| formatted_difftime | Format difftime objects |
| generate_bandit_data | Bandit: Superclass |
| get_action | Policy: Superclass |
| get_arm_context | Return context vector of an arm |
| get_context | Bandit: Superclass |
| get_data_frame | History |
| get_data_table | History |
| get_full_context | Get full context matrix over all arms |
| get_global_seed | Lookup .Random.seed in global environment |
| get_t | Agent |
| gg_color_hue | Plot |
| gittinsbrezzilai | Policy: Gittins Approximation algorithm for choosing arms in a MAB problem. |
| GittinsBrezziLaiPolicy | Policy: Gittins Approximation algorithm for choosing arms in a MAB problem. |
| GradientPolicy | Policy: Gradient |
| History | History |
| inc<- | Increment |
| ind | On-the-fly indicator function for use in formulae |
| initialize_theta | Policy: Superclass |
| inv | Inverse from Choleski (or QR) Decomposition. |
| invgamma | The Inverse Gamma Distribution |
| invlogit | Inverse Logit Function |
| is_rstudio | Check if in RStudio |
| LifPolicy | Policy: Continuum Bandit Policy with Lock-in Feedback |
| LinUCBDisjointOptimizedPolicy | Policy: LinUCB with unique linear models |
| LinUCBDisjointPolicy | Policy: LinUCB with unique linear models |
| LinUCBGeneralPolicy | Policy: LinUCB with unique linear models |
| LinUCBHybridOptimizedPolicy | Policy: LinUCB with hybrid linear models |
| LinUCBHybridPolicy | Policy: LinUCB with hybrid linear models |
| load | History |
| mvrnorm | Simulate from a Multivariate Normal Distribution |
| OfflineBootstrappedReplayBandit | Bandit: Offline Bootstrapped Replay |
| OfflineDirectMethodBandit | Bandit: Offline Direct Methods |
| OfflineDoublyRobustBandit | Bandit: Offline Doubly Robust |
| OfflineLookupReplayEvaluatorBandit | Bandit: Offline Replay with lookup tables |
| OfflinePropensityWeightingBandit | Bandit: Offline Propensity Weighted Replay |
| OfflineReplayEvaluatorBandit | Bandit: Offline Replay |
| ones_in_zeroes | A vector of zeroes and ones |
| one_hot | One Hot Encoding of data.table columns |
| optimal | Plot |
| OraclePolicy | Policy: Oracle |
| pinvgamma | The Inverse Gamma Distribution |
| Plot | Plot |
| plot.History | Plot Method for Contextual History |
| plot.history | Plot Method for Contextual History |
| Policy | Policy: Superclass |
| policy | Policy: Superclass |
| post_initialization | Bandit: Superclass |
| print.History | Print Method for Contextual History |
| print.history | Print Method for Contextual History |
| print_data | History |
| prob_winner | Binomial Win Probability |
| qinvgamma | The Inverse Gamma Distribution |
| RandomPolicy | Policy: Random |
| rinvgamma | The Inverse Gamma Distribution |
| run | Simulator |
| sample_one_of | Sample one element from vector or list |
| save | History |
| set_data_frame | History |
| set_data_table | History |
| set_external | Change Default Graphing Device from RStudio |
| set_global_seed | Set .Random.seed to a pre-saved value |
| set_parameters | Policy: Superclass |
| set_reward | Policy: Superclass |
| set_t | Agent |
| sherman_morrisson | Sherman-Morrisson inverse |
| Simulator | Simulator |
| simulator | Simulator |
| sim_post | Binomial Posterior Simulator |
| SoftmaxPolicy | Policy: Softmax |
| summary.History | Summary Method for Contextual History |
| summary.history | Summary Method for Contextual History |
| sum_of | Sum of list |
| theta | Policy: Superclass |
| ThompsonSamplingPolicy | Policy: Thompson Sampling |
| UCB1Policy | Policy: UCB1 |
| UCB2Policy | Policy: UCB2 |
| value_remaining | Potential Value Remaining |
| var_welford | Welford's variance |
| which_max_list | Get maximum value in list |
| which_max_tied | Get maximum value randomly breaking ties |