Principal components are a well established tool in dimension reduction. The extension to principal
curves allows for general smooth curves which pass through the middle of a multidimensional data
cloud. In this paper local principal curves are introduced, which are based on the localization of
principal component analysis. The proposed algorithm is able to identify closed curves as well as
multiple curveswhich may ormay not be connected. For the evaluation of the performance of principal
curves as tool for data reduction a measure of coverage is suggested. By use of simulated and real
data sets the approach is compared to various alternative concepts of principal curves
Is data on this page outdated, violates copyrights or anything else? Report the problem now and we will take corresponding actions after reviewing your request.