Using Functional Data Analysis (FDA) Methodology and the R Package “fda” for Sensory Time‐Intensity Evaluation

Abstract 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.