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The goal of SIHR is to provide inference procedures in the high-dimensional generalized linear regression setting for:
(1) linear functionals <doi:10.48550/arXiv.1904.12891> <doi:10.48550/arXiv.2012.07133>,
(2) conditional average treatment effects,
(3) quadratic functionals <doi:10.48550/arXiv.1909.01503>,
(4) inner product,
(5) distance.

Zijian Guo 

SIHR

Statistical Inference in High Dimensional Regression

Zhenyu Wang

Prabrisha Rakshit

Tony Cai

Zijian Guo

ci function

<dl><dt>object</dt>
<dd>An object of class</dd>
<dt>probability</dt>
<dd>Whether returns CI with probability transformation or not
(default=<code>FALSE</code>)</dd>
<dt>alpha</dt>
<dd>Level of significance to construct confidence interval
(default=0.05)</dd>
<dt>alternative</dt>
<dd>Indicates the alternative hypothesis to construct
confidence interval and must be one of "two.sided" (default), "less", or
"greater".</dd>
<dt>...</dt>
<dd>arguments to pass down</dd></dl>

Arguments

Confidence Intervals for Bias-corrected Estimators — ci

<dl>

<dt>object</dt>
<dd>An object of class</dd>


<dt>probability</dt>
<dd>Whether returns CI with probability transformation or not
(default=<code>FALSE</code>)</dd>


<dt>alpha</dt>
<dd>Level of significance to construct confidence interval
(default=0.05)</dd>


<dt>alternative</dt>
<dd>Indicates the alternative hypothesis to construct
confidence interval and must be one of "two.sided" (default), "less", or
"greater".</dd>


<dt>...</dt>
<dd>arguments to pass down</dd>

</dl>

Confidence Intervals for Bias-corrected Estimators

ci: Confidence Intervals for Bias-corrected Estimators

Description

Usage

Arguments