Quantile Models

init_notebook_modetrusted

QTE

The results are based on a location-scale model as described the corresponding Example with \(5000\) observations.

The non-uniform results (coverage, ci length and bias) refer to averaged values over all quantiles (point-wise confidende intervals).

Metadata

DoubleML Version                         0.11.dev0
Script                        PQCoverageSimulation
Date                              2025-09-08 08:35
Total Runtime (minutes)                 117.055629
Python Version                              3.12.3
Config File              scripts/irm/pq_config.yml

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Potential Quantiles

Y(0) - Quantile

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Y(1) - Quantile

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LQTE

The results are based on a location-scale model as described the corresponding Example with \(5,000\) observations.

The non-uniform results (coverage, ci length and bias) refer to averaged values over all quantiles (point-wise confidende intervals).

Metadata

DoubleML Version                          0.11.dev0
Script                        LPQCoverageSimulation
Date                               2025-09-08 08:32
Total Runtime (minutes)                  114.005955
Python Version                               3.12.3
Config File              scripts/irm/lpq_config.yml

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Local Potential Quantiles

Local Y(0) - Quantile

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Local Y(1) - Quantile

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CVaR Effects

The results are based on a location-scale model as described the corresponding Example with \(5,000\) observations. Remark that the process is not linear.

The non-uniform results (coverage, ci length and bias) refer to averaged values over all quantiles (point-wise confidende intervals).

Metadata

DoubleML Version                           0.11.dev0
Script                        CVARCoverageSimulation
Date                                2025-09-08 08:12
Total Runtime (minutes)                    94.279191
Python Version                                3.12.3
Config File              scripts/irm/cvar_config.yml

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CVaR Potential Quantiles

CVaR Y(0)

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CVaR Y(1)

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