shifted_peaks

<p>A simulated dataset generated for examples in the veesa pipeline manuscript. 
For the code used to prepare this dataset, see
https://github.com/sandialabs/veesa/inst/data-shifted-peaks.md.</p>

datasets

Implements the Variable importance Explainable Elastic Shape Analysis pipeline for explainable machine learning with functional data inputs. Converts training and testing data functional inputs to elastic shape analysis principal components that account for vertical and/or horizontal variability. Computes feature importance to identify important principal components and visualizes variability captured by functional principal components. See Goode et al. (2025) <doi:10.48550/arXiv.2501.07602> for technical details about the methodology.

Katherine Goode

veesa

Pipeline for Explainable Machine Learning with Functional Data

J. Derek Tucker

Sandia National Laboratories 

shifted_peaks function

Format

"Shifted Peaks" Simulated Dataset — shifted_peaks

"Shifted Peaks" Simulated Dataset

`data`	Data frame containing simulated data
`params`	The parameters used to generate the data
`true_means`	The true functional means of the shifted peaks groups.

shifted_peaks: "Shifted Peaks" Simulated Dataset

Description

Usage

Arguments

Format

Details