Statistical properties of convex clustering.
In this manuscript, we study the statistical properties ofconvex clustering. We establish that convex clustering is closely related to single linkage hierarchical clustering andk-means clustering. In addition, we derive the range of the tuning parameter for convex clustering that yields a non-trivial solution. We also provide an unbiased estimator of the degrees of freedom, and provide a finite sample bound for the prediction error for convex clustering. We compare convex clustering to some traditional clustering methods in simulation studies.
Department of Biostatistics, University of Washington, Seattle, WA 98195, U.S.A., keanming@uw.edu.
Kean Ming
KM
Tan
Departments of Statistics and Biostatistics, University of Washington, Seattle, WA 98195, U.S.A., dwitten@uw.edu.
Daniela
D
Witten
Degrees of freedom; fusion penalty; hierarchical clustering; k-means; prediction error; single linkage