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Using Functional Data Analysis (FDA) Methodology and the R Package “fda” for Sensory Time‐Intensity Evaluation
Author(s) -
Bi Jian,
Kuesten Carla
Publication year - 2013
Publication title -
journal of sensory studies
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.61
H-Index - 53
eISSN - 1745-459X
pISSN - 0887-8250
DOI - 10.1111/joss.12072
Subject(s) - sensory analysis , functional data analysis , sensory system , computer science , univariate , machine learning , multivariate statistics , statistics , mathematics , psychology , cognitive psychology
Measuring and analyzing time‐intensity ( T ‐ I ) of sensory attributes is an important subject of sensory analysis. This paper proposes using functional data analysis ( FDA ), an emerging field in statistical research, as a new strategy and framework for sensory T ‐ I data analysis. This paper discusses and illustrates how to apply the well‐developed FDA techniques and use the available R package “fda” to analyze sensory T ‐ I data. The analyses include data smoothing, descriptions of functional data, functional regression analysis, functional analysis of variance and permutation tests of functional hypotheses (functional F ‐tests and t ‐tests). Some conclusions about applications of FDA to sensory T ‐ I data are reached. Practical Applications The currently used statistical analysis for sensory T ‐ I data is not well developed. There are some limitations of using univariate and multivariate data analyses for sensory T ‐ I data. FDA is a promising alternative. This paper shows some advantages using FDA and the R package “fda” for the analysis of sensory T ‐ I data. It is expected that the introduction and application of FDA in the sensory field will dramatically improve data analysis for T ‐ I evaluation of sensory attributes.