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causalis.data_contracts
  • CausalData
  • CausalDataInstrumental
  • CausalDatasetGenerator
  • CausalEstimate
  • DiagnosticData
  • MultiCausalData
  • RegressionChecks
  • UnconfoundednessDiagnosticData
  • causal_diagnostic_data
  • causal_estimate
  • causaldata
  • causaldata_instrumental
  • classic_rct_gamma
  • classic_rct_gamma_26
  • generate_classic_rct
  • generate_classic_rct_26
  • generate_cuped_binary
  • generate_rct
  • make_cuped_binary_26
  • make_gold_linear
  • multicausal_estimate
  • multicausaldata
  • obs_linear_26_dataset
  • obs_linear_effect
  • regression_checks
causalis.dgp
  • CausalDatasetGenerator
  • base
  • causaldata
  • causaldata_instrumental
  • classic_rct_gamma
  • classic_rct_gamma_26
  • generate_classic_rct
  • generate_classic_rct_26
  • generate_cuped_binary
  • generate_cuped_tweedie_26
  • generate_iv_data
  • generate_rct
  • make_cuped_binary_26
  • make_cuped_tweedie
  • make_gold_linear
  • multicausaldata
  • obs_linear_26_dataset
  • obs_linear_effect
causalis.scenarios
  • cate
  • classic_rct
  • cuped
  • multi_unconfoundedness
  • unconfoundedness
causalis.shared
  • QUESTIONS
  • SRMResult
  • check_srm
  • confounders_balance
  • outcome_outliers
  • outcome_plot_boxplot
  • outcome_plot_dist
  • outcome_plots
  • outcome_stats
  • print_sutva_questions
  • rct_design
  • srm
  • sutva_validation
  1. API Reference
  2. causalis.dgp
  3. base
API ReferenceEntry

base

base

Reference details for base in causalis.dgp.

base

Functions
  • estimate_gaussian_copula_corr – Estimate a Gaussian copula correlation matrix from observational data_contracts.
estimate_gaussian_copula_corr

Estimate a Gaussian copula correlation matrix from observational data_contracts. Uses rank -> normal scores -> Pearson correlation approach.