find_root

This function is used internally by the function compute_ci_with_specified_interval for inverting post-selection p-values to confidence intervals.

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

find_root 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>tn_sigma</dt>
<dd>Integer for the variance of the truncated sampling distribution of the test statistic</dd>
 
 <dt>y</dt>
<dd>For example 1.0-0.5*alpha for finding the lower bound of a (1-alpha)% confidence interval, and 0.5*alpha for finding the upper bound of a (1-alpha)% confidence interval</dd>
 
 <dt>lb</dt>
<dd>Lower bound in current iteration</dd> <dt>ub</dt>
<dd>Upper bound in current iteration</dd> <dt>tol</dt>
<dd>Tolerance parameter: default set to 1e-6</dd></dl>

Arguments

Find root — find_root

<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>tn_sigma</dt>
<dd>Integer for the variance of the truncated sampling distribution of the test statistic</dd>
 
 <dt>y</dt>
<dd>For example 1.0-0.5*alpha for finding the lower bound of a (1-alpha)% confidence interval, and 0.5*alpha for finding the upper bound of a (1-alpha)% confidence interval</dd>
 
 <dt>lb</dt>
<dd>Lower bound in current iteration</dd>

 <dt>ub</dt>
<dd>Upper bound in current iteration</dd>

 <dt>tol</dt>
<dd>Tolerance parameter: default set to 1e-6</dd>

</dl>

find_root: Find root

Description

Usage

Value

Arguments

References