Functional Principal Components Analysis and the Capacity CoefficientThe 43rd Annual Meeting of the Society for Mathematical Psychology (2010)
AbstractThe capacity coefficient is a well established measure of the efficiency of processing combined sources of information. It has been applied to measure cognitive processes ranging from audio-visual integration to face perception. Recently, the capacity coefficient has also been applied in various clinical situations. Typical clinical analysis, such as structural equation modeling, use scalar values or vectors with limited length as input. We explored the use of functional principal component analysis (fPCA) to allow researchers to describe the capacity coefficient, a continuous function of time, with a small set of discrete values. The fPCA approach was compared with two simple alternatives for reducing the capacity coefficient to a single value. We found that fPCA captured the major trends in the data more effectively than other methods.
- capacity coefficient,
- functional principal component analysis,
Publication DateAugust, 2010
Citation InformationD. Burns, Joseph W Houpt, M. J. Endres and J. T. Townsend. "Functional Principal Components Analysis and the Capacity Coefficient" The 43rd Annual Meeting of the Society for Mathematical Psychology (2010)
Available at: http://works.bepress.com/joseph_houpt/19/