Analysis of Functional Responses in Experimental Design

The growth of sensor streamed data in recent years increases the demand for an analytical technique to properly address data measured continuously. The design and analysis of experiments (DOE) of U.S. Air Force assets are based off of sensor streamed data. Functional data analysis (FDA) is an approach of analyzing data existing over a continuum. This research aids in filling the intersection of FDA and DOE by examining a case study of an experimental design with a functional response in addition to insight on software capabilities in FDA. The case study considers a functional linear model of a whole-plot from a split-plot experimental design compared to multivariate methods and an approximated functional linear model. Initial results indicate no signifixC;cant main effects were detected in the case study using FDA. However, a comparison between the different methodologies indicate similar behaviors for main effect estimates. An examination of software packages reveals the R software as most compatible with FDA methodology. Recommendations include another case study evaluation of FDA and future work in alignment of response curves