z-logo
Premium
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.

This content is not available in your region!

Continue researching here.

Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom