Function used internally by compute_ci_with_specified_interval for calculating valid confidence intervals post-selection.

models

regression

htest

Conduct post-selection inference for regression coefficients in linear models after they have been selected by adjusted R squared. The p-values and confidence intervals are valid after model selection with the same data. This allows the user to use all data for both model selection and inference without losing control over the type I error rate. The provided tests are more powerful than data splitting, which bases inference on less data since it discards all information used for selection.

Sarah Pirenne

PoSIAdjRSquared

Post-Selection Inference for Adjusted R Squared

Gerda Claeskens

f function

<dl> <dt>z_interval</dt>
<dd>The intervals of type "list" where the OLS estimator gets selected: can be obtained from function "solve_selection_event"</dd> <dt>etajTy</dt>
<dd>The OLS estimator of the j'th selected coefficient in the selected model of type "matrix" and dimension 1x1</dd> <dt>mu</dt>
<dd>Integer for the mean of the truncated sampling distribution of the test statistic (updated iteratively in compute_ci_with_specified_interval)</dd> <dt>tn_sigma</dt>
<dd>Integer for the variance of the truncated sampling distribution of the test statistic</dd></dl>

Arguments

f — f

<dl>

 <dt>z_interval</dt>
<dd>The intervals of type "list" where the OLS estimator gets selected: can be obtained from function "solve_selection_event"</dd>

 <dt>etajTy</dt>
<dd>The OLS estimator of the j'th selected coefficient in the selected model of type "matrix" and dimension 1x1</dd>

 <dt>mu</dt>
<dd>Integer for the mean of the truncated sampling distribution of the test statistic (updated iteratively in compute_ci_with_specified_interval)</dd>

 <dt>tn_sigma</dt>
<dd>Integer for the variance of the truncated sampling distribution of the test statistic</dd>

</dl>

f: f

Description

Value

Arguments

References