PLPR Models

Coverage

The simulations are based on the the make_plpr_CP2025-DGP with \(1000\) units and \(10\) time periods. The following DGPs are considered:

  • DGP 1: Linear in the nuisance parameters
  • DGP 2: Non-linear and smooth in the nuisance parameters
  • DGP 3: Non-linear and discontinuous in the nuisance parameters
DoubleML Version                            0.11.2.dev96
Script                         PLPRATECoverageSimulation
Date                                    2026-01-16 15:02
Total Runtime (minutes)                         36.61475
Python Version                                    3.12.9
Config File              scripts/plm/plpr_ate_config.yml

Partialling out

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IV-type

For the IV-type score, the learners ml_l and ml_g are both set to the same type of learner (here Learner g).

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Tuning

The simulations are based on the the make_plpr_CP2025-DGP with \(1000\) units and \(10\) time periods. The following DGPs are considered:

  • DGP 1: Linear in the nuisance parameters
  • DGP 3: Non-linear and discontinuous in the nuisance parameters

This is only an example as the untuned version just relies on the default configuration.

DoubleML Version                                 0.11.2.dev96
Script                        PLPRATETuningCoverageSimulation
Date                                         2026-01-16 16:54
Total Runtime (minutes)                             76.147265
Python Version                                         3.12.9
Config File              scripts/plm/plpr_ate_tune_config.yml

Partialling out

Loading ITables v2.6.2 from the init_notebook_mode cell... (need help?)
Loading ITables v2.6.2 from the init_notebook_mode cell... (need help?)