In this study, we compared age-related lip movement variability with acoustic variability across repetitions using Functional Data Analysis (FDA). Lip movement and acoustic data of 1520 repetitions of a short Swedish phrase from 50 Swedish speakers were collected. Results showed weak to moderate negative correlations for age and variability in lip movements, phrase duration and sound pressure l...

T Bass model has been a standard for analyzing and predicting the market penetration of new products. We demonstrate the insights to be gained and predictive performance of functional data analysis (FDA), a new class of nonparametric techniques that has shown impressive results within the statistics community, on the market penetration of 760 categories drawn from 21 products and 70 countries. ...

This paper investigates how expressive gestures of a professional clarinetist contribute to the perception of structure and affect in musical performance. The thirty musically trained subjects saw, heard, or both saw and heard the performance. All subjects made the same judgments including a real-time judgment of phrasing, which targeted the experience of structure, and a real-time judgment of ...

This paper discusses the use of functional data analysis to determine the interactions between the chemical composition and grain size. The proposed method is compared for a case study with others that involve the determination of the coefficient of correlation between the concentration of each chemical element in a bulk sample and representative points in the granulometric curve. The results o...

Functional data analysis is typically performed in two steps: first, functionally representing discrete observations, and then applying functional methods, such as the principal component analysis, to so-represented data. While initial choice of a representation may have significant impact on second phase this issue has not gained much attention past. Typically, rather ad hoc some standard basi...

Functional data analysis is a growing research field and numerous works present a generalization of the classical statistical methods to function classification or regression. In this paper, we focus on the problem of using Support Vector Machines (SVMs) for curve discrimination. We recall that important theoretical results for SVMs apply in functional space and propose simple functional kernel...