Add Sensitivity Analysis #201
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add g_hat1 estimation to ATTE to simplify sensitivity analysis
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| # if not np.all(np.diff(train_index) > 0): | ||
| # raise NotImplementedError('Invalid sample split. Only sorted train indices are supported.') | ||
| # if not np.all(np.diff(test_index) > 0): | ||
| # raise NotImplementedError('Invalid sample split. Only sorted test indices are supported.') |
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Commented-out code
slightly reduce number of unit test for lpq
| @@ -147,6 +147,8 @@ | |||
| self._trimming_threshold = trimming_threshold | |||
| _check_trimming(self._trimming_rule, self._trimming_threshold) | |||
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| self._sensitivity_implemented = True | |||
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Overwriting attribute in super-class or sub-class
| @@ -147,6 +147,8 @@ | |||
| self._trimming_threshold = trimming_threshold | |||
| _check_trimming(self._trimming_rule, self._trimming_threshold) | |||
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| self._sensitivity_implemented = True | |||
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Code scanning / CodeQL
Overwriting attribute in super-class or sub-class
SvenKlaassen
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Description
Adding sensitivity analysis to account for omitted variable bias to PLR, IRM, DID and DIDCS models based on Chernozhukov et al. (2022).
For each specific class the Riesz representer is implmented with method
_sensitivity_element_est()to estimatesensitivity_elements(see guide documentation Sensitivity Analysis doubleml-docs#142).Sensitivity analysis
sensitivity_analysis()method (see guide or example documentation Sensitivity Analysis doubleml-docs#142).Contour plots via
sensitivity_plot()(see guide or example documentation Sensitivity Analysis doubleml-docs#142).Comments
_utils_checkfolderPR Checklist