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 |