Outlier Detection for Functional Data with R Package fdaoutlier

TL;DR

The paper introduces the R package fdaoutlier, which implements advanced techniques for detecting various types of outliers in functional data, facilitating exploratory analysis.

Contribution

It provides an easy-to-use tool with methods applicable to both univariate and multivariate functional data for outlier detection.

Findings

Effective detection of magnitude, shape, and amplitude outliers

Applicable to univariate and multivariate functional data

Demonstrated on common functional datasets

Abstract

Outlier detection is one of the standard exploratory analysis tasks in functional data analysis. We present the R package fdaoutlier which contains implementations of some of the latest techniques for detecting functional outliers. The package makes it easy to detect different types of outliers (magnitude, shape, and amplitude) in functional data, and some of the implemented methods can be applied to both univariate and multivariate functional data. We illustrate the main functionality of the R package with common functional datasets in the literature.