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Data Analysis and Problem Solving Seminar
Data Analysis and Problem Solving Seminar
Exploratory Functional Data Analysis
Exploratory Functional Data Analysis
Organizer
Speaker
Wenlin Dai
Time
Friday, April 24, 2026 3:00 PM - 4:00 PM
Venue
A3-1-301
Online
Zoom 204 323 0165
(BIMSA)
Abstract
With the advance of technology, functional data are being recorded more frequently, whether over one-dimensional or multi-dimensional domains. Due to the high dimensionality and complex features of functional data, exploratory data analysis faces significant challenges. To meet the demands of practical applications, researchers have developed various tools, including visualization tools, outlier detection techniques, and clustering methods that can handle diverse types of functional data. This talk offers a comprehensive overview of recent procedures for exploratory functional data analysis (EFDA). It begins by introducing fundamental statistical concepts, such as mean and covariance functions, as well as robust statistics such as the median and quantiles in multivariate functional data. Then, we review popular visualization methods for functional data, such as the rainbow plot, and various versions of the functional boxplot, each designed to accommodate different features of functional data. In addition to visualization tools, we also review outlier detection methods, which are commonly integrated with visualization methods to identify anomalous patterns within the data. All the reviewed methods have been implemented in an R package named EFDA.