find.sub.argmin

Get the index of the smallest dimension apart from an index

Provides methods to construct frequentist confidence sets with valid marginal
coverage for identifying the population-level argmin or argmax based on IID data.
For instance, given an n by p loss matrix—where n is the sample size and p is the
number of models—the CS.argmin() method produces a discrete confidence set that contains
the model with the minimal (best) expected risk with desired probability. The argmin.HT()
method helps check if a specific model should be included in such a confidence set. The main
implemented method is proposed by Tianyu Zhang, Hao Lee and Jing Lei (2024)
"Winners with confidence: Discrete argmin inference with an application to model selection".

Hao Lee

argminCS

Argmin Inference over a Discrete Candidate Set

Tianyu Zhang

Jing Lei

find.sub.argmin function

<dl><dt>nums</dt>
<dd>A vector of numbers</dd>
<dt>idx</dt>
<dd>An index to be excluded</dd>
<dt>seed</dt>
<dd>(Optional) If provided, used to seed the random sampling (for reproducibility).</dd></dl>

Arguments

Get the index of the smallest dimension apart from an index — find.sub.argmin

<dl>

<dt>nums</dt>
<dd>A vector of numbers</dd>


<dt>idx</dt>
<dd>An index to be excluded</dd>


<dt>seed</dt>
<dd>(Optional) If provided, used to seed the random sampling (for reproducibility).</dd>

</dl>

find.sub.argmin: Get the index of the smallest dimension apart from an index

Description

Usage

Value

Arguments

Examples