Package index
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build_individual_keys()
- Generate individual record keys
Build a counting table and apply the CKM
Functions to build and apply the Cell Key Method, on a single table or a list of tables.
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tabulate_cnt_micro_data()
- Build contingency table with margins from microdata
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apply_ckm()
- Apply Cell Key Method to a contingency table
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tabulate_and_apply_ckm()
- Build table and apply Cell Key Method
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tabulate_and_apply_ckm_list()
- Build tables and apply Cell Key Method on a list
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assess_RU()
- Measure risk and utility for a single scenario
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assess_RUs()
- Compare risk and utility across multiple scenarios
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simulate_RUs()
- Compare risk and utility across multiple scenarios with multiple simulations
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assess_risk()
- Measure risk by estimating inverse transition probabilities
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get_deviation_set()
- Calculate deviation set for a given original value
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get_possibles_set()
- Calculate possible set for a given perturbed value
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compute_frequencies()
- Calculate empirical frequencies from aggregated table
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distance_hellinger()
- Hellinger distance
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mean_absolute_deviation()
- Mean absolute deviations
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mean_relative_absolute_deviation()
- Mean relative absolute deviations in percentage
Compute confidence intervals
Functions providing confidence intervals for statistics built from perturbed counts.
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estimate_beta()
- Estimate minimal precision threshold \(\beta\) for given error level \(\alpha\)
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estimate_beta_df()
- Estimate Confidence Intervals for Ratios Using Beta Distribution
Build the transition matrix and prepare the perturbation table
Functions to retrieve the transition matrix and compare scenarios by visualizing the theoretical noise distribution.
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create_transition_matrix()
- Create Cell Key Method transition matrix
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prepare_perturbation_table()
- Create perturbation table from transition matrix
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test_matrices()
- Test transition matrix construction for different variance values
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visualize_distribution()
- Visualize probability distributions from multiple scenarios
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build_parameters_table()
- Generate parameter combinations table
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convert_desc_table_to_list()
- Convert table description to variable lists
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distance_euclid()
- Euclidean distance
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distance_manhattan()
- Manhattan distance
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estimate_proba_precision_statistic()
- Estimate probability of ratio deviation
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estimate_proba_precision_statistic_df()
- Calculate P(|R-R'|>\(\beta\)), the probability of ratio deviation for a dataframe and given CKM parameter and for each \(\beta\) value.
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dtest
- Sample dataset for CKM package