lvim_autc

Compute a nonparametric estimate of (and efficient influence function for) the
area under the longitudinal variable importance trajectory (AUTC) over a contiguous subset of the time series.

Calculate point estimates of and valid confidence intervals for
longitudinal summaries of nonparametric, algorithm-agnostic variable importance measures.
For more details, see Williamson et al. (2024) <doi:10.48550/arXiv.2311.01638>.

Brian D. Williamson

lvimp

Perform Inference on Summaries of Longitudinal
Algorithm-Agnostic Variable Importance

lvim_autc function

<dl><dt>lvim</dt>
<dd>an object of class <code>lvim</code> containing the cross-sectional
variable importance objects</dd>
<dt>indices</dt>
<dd>a numeric vector indicating the contiguous subset of the
time series</dd>
<dt>interpolator</dt>
<dd>a string indicating the type of interpolator used to
take the area under the trajectory</dd>
<dt>delta</dt>
<dd>null hypothesis value</dd>
<dt>...</dt>
<dd>other arguments to be passed to the interpolator function</dd></dl>

Arguments

Area Under the Variable Importance Trajectory — lvim_autc

<dl>

<dt>lvim</dt>
<dd>an object of class <code>lvim</code> containing the cross-sectional
variable importance objects</dd>


<dt>indices</dt>
<dd>a numeric vector indicating the contiguous subset of the
time series</dd>


<dt>interpolator</dt>
<dd>a string indicating the type of interpolator used to
take the area under the trajectory</dd>


<dt>delta</dt>
<dd>null hypothesis value</dd>


<dt>...</dt>
<dd>other arguments to be passed to the interpolator function</dd>

</dl>

lvim_autc: Area Under the Variable Importance Trajectory

Description

Usage

Value

Arguments