envelope

Code for obtaining the envelope Ji of a curve specified by the index i. The
implementation is based on Algorithm 1 in [1]. References:

Integrated Functional Depth for Partially Observed Functional Data and applications to visualization, outlier detection and classification. It implements the methods proposed in: Elías, A., Jiménez, R., Paganoni, A. M. and Sangalli, L. M., (2023), "Integrated Depth for Partially Observed Functional Data", Journal of Computational and Graphical Statistics, <doi:10.1080/10618600.2022.2070171>. Elías, A., Jiménez, R., & Shang, H. L. (2023), "Depth-based reconstruction method for incomplete functional data", Computational Statistics, <doi:10.1007/s00180-022-01282-9>. Elías, A., Nagy, S. (2024), "Statistical properties of partially observed integrated functional depths", TEST, <doi:10.1007/s11749-024-00954-6>.

Antonio El<c3><ad>as

fdaPOIFD

Partially Observed Integrated Functional Depth

Antonio Elías

Raúl Jiménez

Anna M. Paganoni

Laura M. Sangalli

Stanislav Nagy

Maximiliam Ofner

envelope function

<dl><dt>data</dt>
<dd>Data matrix.</dd>
<dt>i</dt>
<dd>Index of curve.</dd>
<dt>max_iter</dt>
<dd>Maximum number of nearest curves considered in for loop. By
default, max_iter = 5.</dd></dl>

Arguments

Envelope algorithm — envelope

<dl>

<dt>data</dt>
<dd>Data matrix.</dd>


<dt>i</dt>
<dd>Index of curve.</dd>


<dt>max_iter</dt>
<dd>Maximum number of nearest curves considered in for loop. By
default, max_iter = 5.</dd>

</dl>

envelope: Envelope algorithm

Description

Usage

Value

Arguments

Details