| Construct an instance of the 'AbsoluteDistance' metric. | absolute_distance |
| Convert a desired 'accuracy' (tolerance) into a discrete gaussian noise scale at a statistical significance level 'alpha'. | accuracy_to_discrete_gaussian_scale |
| Convert a desired 'accuracy' (tolerance) into a discrete Laplacian noise scale at a statistical significance level 'alpha'. | accuracy_to_discrete_laplacian_scale |
| Convert a desired 'accuracy' (tolerance) into a gaussian noise scale at a statistical significance level 'alpha'. | accuracy_to_gaussian_scale |
| Convert a desired 'accuracy' (tolerance) into a Laplacian noise scale at a statistical significance level 'alpha'. | accuracy_to_laplacian_scale |
| Privacy measure used to define delta-approximate PM-differential privacy. | approximate |
| Construct an instance of 'AtomDomain'. | atom_domain |
| Find the closest passing value to the decision boundary of 'predicate' | binary_search |
| Find the highest-utility ('d_in', 'd_out')-close Transformation or Measurement. | binary_search_chain |
| Solve for the ideal constructor argument to 'make_chain' | binary_search_param |
| type signature for a BitVector | BitVector |
| Construct an instance of 'BitVectorDomain'. | bitvector_domain |
| type signature for a boolean | bool |
| Construct an instance of the 'ChangeOneDistance' metric. | change_one_distance |
| Returns an approximation to the ideal 'branching_factor' for a dataset of a given size, that minimizes error in cdf and quantile estimates based on b-ary trees. | choose_branching_factor |
| Disable features in the opendp package. | disable_features |
| Construct an instance of the 'DiscreteDistance' metric. | discrete_distance |
| Convert a discrete gaussian scale into an accuracy estimate (tolerance) at a statistical significance level 'alpha'. | discrete_gaussian_scale_to_accuracy |
| Convert a discrete Laplacian scale into an accuracy estimate (tolerance) at a statistical significance level 'alpha'. | discrete_laplacian_scale_to_accuracy |
| Get the carrier type of a 'domain'. | domain_carrier_type |
| Debug a 'domain'. | domain_debug |
| Get the type of a 'domain'. | domain_type |
| Enable features for the opendp package. | enable_features |
| type signature for an arbitrary R object preserved across FFI | ExtrinsicObject |
| type signature for a 32-bit floating point number | f32 |
| type signature for a 64-bit floating point number | f64 |
| Privacy measure used to define (epsilon, delta)-approximate differential privacy. | fixed_smoothed_max_divergence |
| Eval the 'function' with 'arg'. | function_eval |
| Convert a gaussian scale into an accuracy estimate (tolerance) at a statistical significance level 'alpha'. | gaussian_scale_to_accuracy |
| Construct an instance of the 'HammingDistance' metric. | hamming_distance |
| extract heterogeneously typed keys and values from a hashtab | hashitems |
| type signature for a 128-bit signed integer | i128 |
| type signature for a 16-bit signed integer | i16 |
| type signature for a 32-bit signed integer | i32 |
| type signature for a 64-bit signed integer | i64 |
| type signature for an 8-bit signed integer | i8 |
| Construct an instance of the 'InsertDeleteDistance' metric. | insert_delete_distance |
| Construct an instance of the 'L01InfDistance' metric. | l01inf_distance |
| Construct an instance of the 'L02InfDistance' metric. | l02inf_distance |
| Construct an instance of the 'L1Distance' metric. | l1_distance |
| Construct an instance of the 'L2Distance' metric. | l2_distance |
| Convert a Laplacian scale into an accuracy estimate (tolerance) at a statistical significance level 'alpha'. | laplacian_scale_to_accuracy |
| Construct an instance of the 'LInfDistance' metric. | linf_distance |
| adaptive composition constructor | make_adaptive_composition |
| alp queryable constructor | make_alp_queryable |
| approximate constructor | make_approximate |
| b ary tree constructor | make_b_ary_tree |
| basic composition constructor | make_basic_composition |
| bounded float checked sum constructor | make_bounded_float_checked_sum |
| bounded float ordered sum constructor | make_bounded_float_ordered_sum |
| bounded int monotonic sum constructor | make_bounded_int_monotonic_sum |
| bounded int ordered sum constructor | make_bounded_int_ordered_sum |
| bounded int split sum constructor | make_bounded_int_split_sum |
| canonical noise constructor | make_canonical_noise |
| cast constructor | make_cast |
| cast default constructor | make_cast_default |
| cast inherent constructor | make_cast_inherent |
| cdf constructor | make_cdf |
| chain mt constructor | make_chain_mt |
| chain pm constructor | make_chain_pm |
| chain tt constructor | make_chain_tt |
| clamp constructor | make_clamp |
| composition constructor | make_composition |
| consistent b ary tree constructor | make_consistent_b_ary_tree |
| count constructor | make_count |
| count by constructor | make_count_by |
| count by categories constructor | make_count_by_categories |
| count distinct constructor | make_count_distinct |
| create dataframe constructor | make_create_dataframe |
| df cast default constructor | make_df_cast_default |
| df is equal constructor | make_df_is_equal |
| drop null constructor | make_drop_null |
| find constructor | make_find |
| find bin constructor | make_find_bin |
| fix delta constructor | make_fix_delta |
| fixed approxDP to approxDP constructor | make_fixed_approxDP_to_approxDP |
| fully adaptive composition constructor | make_fully_adaptive_composition |
| gaussian constructor | make_gaussian |
| gaussian threshold constructor | make_gaussian_threshold |
| geometric constructor | make_geometric |
| identity constructor | make_identity |
| impute constant constructor | make_impute_constant |
| impute uniform float constructor | make_impute_uniform_float |
| index constructor | make_index |
| is equal constructor | make_is_equal |
| is null constructor | make_is_null |
| laplace constructor | make_laplace |
| laplace threshold constructor | make_laplace_threshold |
| lipschitz float mul constructor | make_lipschitz_float_mul |
| mean constructor | make_mean |
| metric bounded constructor | make_metric_bounded |
| metric unbounded constructor | make_metric_unbounded |
| noise constructor | make_noise |
| noise threshold constructor | make_noise_threshold |
| noisy max constructor | make_noisy_max |
| noisy top k constructor | make_noisy_top_k |
| ordered random constructor | make_ordered_random |
| population amplification constructor | make_population_amplification |
| privacy filter constructor | make_privacy_filter |
| private quantile constructor | make_private_quantile |
| pureDP to zCDP constructor | make_pureDP_to_zCDP |
| quantile score candidates constructor | make_quantile_score_candidates |
| quantiles from counts constructor | make_quantiles_from_counts |
| randomized response constructor | make_randomized_response |
| randomized response bitvec constructor | make_randomized_response_bitvec |
| randomized response bool constructor | make_randomized_response_bool |
| report noisy max gumbel constructor | make_report_noisy_max_gumbel |
| resize constructor | make_resize |
| select column constructor | make_select_column |
| select private candidate constructor | make_select_private_candidate |
| sequential composition constructor | make_sequential_composition |
| sized bounded float checked sum constructor | make_sized_bounded_float_checked_sum |
| sized bounded float ordered sum constructor | make_sized_bounded_float_ordered_sum |
| sized bounded int checked sum constructor | make_sized_bounded_int_checked_sum |
| sized bounded int monotonic sum constructor | make_sized_bounded_int_monotonic_sum |
| sized bounded int ordered sum constructor | make_sized_bounded_int_ordered_sum |
| sized bounded int split sum constructor | make_sized_bounded_int_split_sum |
| split dataframe constructor | make_split_dataframe |
| split lines constructor | make_split_lines |
| split records constructor | make_split_records |
| subset by constructor | make_subset_by |
| sum constructor | make_sum |
| sum of squared deviations constructor | make_sum_of_squared_deviations |
| unordered constructor | make_unordered |
| user measurement constructor | make_user_measurement |
| user transformation constructor | make_user_transformation |
| variance constructor | make_variance |
| zCDP to approxDP constructor | make_zCDP_to_approxDP |
| Construct an instance of 'MapDomain'. | map_domain |
| Privacy measure used to define epsilon-pure differential privacy. | max_divergence |
| Debug a 'measure'. | measure_debug |
| Get the distance type of a 'measure'. | measure_distance_type |
| Get the type of a 'measure'. | measure_type |
| Check the privacy relation of the 'measurement' at the given 'd_in', 'd_out' | measurement_check |
| Get the function from a measurement. | measurement_function |
| Get the input (carrier) data type of 'this'. | measurement_input_carrier_type |
| Get the input distance type of 'measurement'. | measurement_input_distance_type |
| Get the input domain from a 'measurement'. | measurement_input_domain |
| Get the input domain from a 'measurement'. | measurement_input_metric |
| Invoke the 'measurement' with 'arg'. Returns a differentially private release. | measurement_invoke |
| Use the 'measurement' to map a given 'd_in' to 'd_out'. | measurement_map |
| Get the output distance type of 'measurement'. | measurement_output_distance_type |
| Get the output domain from a 'measurement'. | measurement_output_measure |
| Debug a 'metric'. | metric_debug |
| Get the distance type of a 'metric'. | metric_distance_type |
| Get the type of a 'metric'. | metric_type |
| new domain | new_domain |
| Construct a Function from a user-defined callback. Can be used to build a postprocessor. | new_function |
| new function | new_function_internal |
| create an instance of a hashtab from keys and values | new_hashtab |
| new measure | new_measure |
| new measurement | new_measurement |
| new metric | new_metric |
| new odometer | new_odometer |
| new odometer queryable | new_odometer_queryable_internal |
| Construct a PrivacyProfile from a user-defined callback. | new_privacy_profile |
| new privacy profile | new_privacy_profile_internal |
| Construct a queryable from a user-defined transition function. | new_queryable |
| new queryable | new_queryable_internal |
| new transformation | new_transformation |
| Internal function. Retrieve the type descriptor string of an AnyObject. | object_type |
| Get the input (carrier) data type of 'this'. | odometer_input_carrier_type |
| Get the input domain from a 'odometer'. | odometer_input_domain |
| Get the input domain from a 'odometer'. | odometer_input_metric |
| Invoke the 'odometer' with 'arg'. Returns a differentially private release. | odometer_invoke |
| Get the output domain from a 'odometer'. | odometer_output_measure |
| Eval the odometer 'queryable' with an invoke 'query'. | odometer_queryable_invoke |
| Get the invoke query type of an odometer 'queryable'. | odometer_queryable_invoke_type |
| Retrieve the privacy loss of an odometer 'queryable'. | odometer_queryable_privacy_loss |
| Get the map query type of an odometer 'queryable'. | odometer_queryable_privacy_loss_type |
| OpenDP R Bindings | opendp-package opendp |
| Construct an instance of 'OptionDomain'. | option_domain |
| Parse a runtime type or infer it from an example | parse_or_infer |
| Internal function. Use a PrivacyProfile to find epsilon at a given 'epsilon'. | privacy_profile_delta |
| Internal function. Use an PrivacyProfile to find epsilon at a given 'delta'. | privacy_profile_epsilon |
| Eval the 'queryable' with 'query'. Returns a differentially private release. | queryable_eval |
| Get the query type of 'queryable'. | queryable_query_type |
| Privacy measure used to define epsilon(alpha)-Rényi differential privacy. | renyi_divergence |
| Infer a runtime type from a public example | rt_infer |
| Parse a runtime type descriptor into a runtime_type object | rt_parse |
| Privacy measure used to define epsilon(delta)-approximate differential privacy. | smoothed_max_divergence |
| type signature for a string | String |
| Construct an instance of the 'SymmetricDistance' metric. | symmetric_distance |
| partial adaptive composition constructor | then_adaptive_composition |
| partial alp queryable constructor | then_alp_queryable |
| partial approximate constructor | then_approximate |
| partial b ary tree constructor | then_b_ary_tree |
| partial basic composition constructor | then_basic_composition |
| partial bounded float checked sum constructor | then_bounded_float_checked_sum |
| partial bounded float ordered sum constructor | then_bounded_float_ordered_sum |
| partial bounded int monotonic sum constructor | then_bounded_int_monotonic_sum |
| partial bounded int ordered sum constructor | then_bounded_int_ordered_sum |
| partial bounded int split sum constructor | then_bounded_int_split_sum |
| partial canonical noise constructor | then_canonical_noise |
| partial cast constructor | then_cast |
| partial cast default constructor | then_cast_default |
| partial cast inherent constructor | then_cast_inherent |
| partial cdf constructor | then_cdf |
| partial chain mt constructor | then_chain_mt |
| partial chain pm constructor | then_chain_pm |
| partial chain tt constructor | then_chain_tt |
| partial clamp constructor | then_clamp |
| partial composition constructor | then_composition |
| partial consistent b ary tree constructor | then_consistent_b_ary_tree |
| partial count constructor | then_count |
| partial count by constructor | then_count_by |
| partial count by categories constructor | then_count_by_categories |
| partial count distinct constructor | then_count_distinct |
| partial create dataframe constructor | then_create_dataframe |
| partial df cast default constructor | then_df_cast_default |
| partial df is equal constructor | then_df_is_equal |
| partial drop null constructor | then_drop_null |
| partial find constructor | then_find |
| partial find bin constructor | then_find_bin |
| partial fix delta constructor | then_fix_delta |
| partial fixed approxDP to approxDP constructor | then_fixed_approxDP_to_approxDP |
| partial fully adaptive composition constructor | then_fully_adaptive_composition |
| partial gaussian constructor | then_gaussian |
| partial gaussian threshold constructor | then_gaussian_threshold |
| partial geometric constructor | then_geometric |
| partial identity constructor | then_identity |
| partial impute constant constructor | then_impute_constant |
| partial impute uniform float constructor | then_impute_uniform_float |
| partial index constructor | then_index |
| partial is equal constructor | then_is_equal |
| partial is null constructor | then_is_null |
| partial laplace constructor | then_laplace |
| partial laplace threshold constructor | then_laplace_threshold |
| partial lipschitz float mul constructor | then_lipschitz_float_mul |
| partial mean constructor | then_mean |
| partial metric bounded constructor | then_metric_bounded |
| partial metric unbounded constructor | then_metric_unbounded |
| partial noise constructor | then_noise |
| partial noise threshold constructor | then_noise_threshold |
| partial noisy max constructor | then_noisy_max |
| partial noisy top k constructor | then_noisy_top_k |
| partial ordered random constructor | then_ordered_random |
| partial population amplification constructor | then_population_amplification |
| Compose a measurement with a postprocessing function. | then_postprocess |
| partial privacy filter constructor | then_privacy_filter |
| partial private quantile constructor | then_private_quantile |
| partial pureDP to zCDP constructor | then_pureDP_to_zCDP |
| partial quantile score candidates constructor | then_quantile_score_candidates |
| partial quantiles from counts constructor | then_quantiles_from_counts |
| partial randomized response constructor | then_randomized_response |
| partial randomized response bitvec constructor | then_randomized_response_bitvec |
| partial randomized response bool constructor | then_randomized_response_bool |
| partial report noisy max gumbel constructor | then_report_noisy_max_gumbel |
| partial resize constructor | then_resize |
| partial select column constructor | then_select_column |
| partial select private candidate constructor | then_select_private_candidate |
| partial sequential composition constructor | then_sequential_composition |
| partial sized bounded float checked sum constructor | then_sized_bounded_float_checked_sum |
| partial sized bounded float ordered sum constructor | then_sized_bounded_float_ordered_sum |
| partial sized bounded int checked sum constructor | then_sized_bounded_int_checked_sum |
| partial sized bounded int monotonic sum constructor | then_sized_bounded_int_monotonic_sum |
| partial sized bounded int ordered sum constructor | then_sized_bounded_int_ordered_sum |
| partial sized bounded int split sum constructor | then_sized_bounded_int_split_sum |
| partial split dataframe constructor | then_split_dataframe |
| partial split lines constructor | then_split_lines |
| partial split records constructor | then_split_records |
| partial subset by constructor | then_subset_by |
| partial sum constructor | then_sum |
| partial sum of squared deviations constructor | then_sum_of_squared_deviations |
| partial unordered constructor | then_unordered |
| partial user measurement constructor | then_user_measurement |
| partial user transformation constructor | then_user_transformation |
| partial variance constructor | then_variance |
| partial zCDP to approxDP constructor | then_zCDP_to_approxDP |
| Convert a format-able value to a string representation | to_str.default |
| Convert hashtab to a string representation | to_str.hashtab |
| Convert a 'make_' constructor into a 'then_' constructor. | to_then |
| Check the privacy relation of the 'measurement' at the given 'd_in', 'd_out' | transformation_check |
| Get the function from a transformation. | transformation_function |
| Get the input (carrier) data type of 'this'. | transformation_input_carrier_type |
| Get the input distance type of 'transformation'. | transformation_input_distance_type |
| Get the input domain from a 'transformation'. | transformation_input_domain |
| Get the input domain from a 'transformation'. | transformation_input_metric |
| Invoke the 'transformation' with 'arg'. Returns a differentially private release. | transformation_invoke |
| Use the 'transformation' to map a given 'd_in' to 'd_out'. | transformation_map |
| Get the output distance type of 'transformation'. | transformation_output_distance_type |
| Get the output domain from a 'transformation'. | transformation_output_domain |
| Get the output domain from a 'transformation'. | transformation_output_metric |
| type signature for a 128-bit unsigned integer | u128 |
| type signature for a 16-bit unsigned integer | u16 |
| type signature for a 32-bit unsigned integer | u32 |
| type signature for a 64-bit unsigned integer | u64 |
| type signature for an 8-bit unsigned integer | u8 |
| Construct a new UserDistance. Any two instances of an UserDistance are equal if their string descriptors are equal. | user_distance |
| Privacy measure with meaning defined by an OpenDP Library user (you). | user_divergence |
| Construct a new UserDomain. Any two instances of an UserDomain are equal if their string descriptors are equal. Contains a function used to check if any value is a member of the domain. | user_domain |
| type signature for a pointer-sized unsigned integer | usize |
| Construct an instance of 'VectorDomain'. | vector_domain |
| Privacy measure used to define rho-zero concentrated differential privacy. | zero_concentrated_divergence |
