Large ecological data matrices may be incomplete for various reasons, preventing the use of standard multidimensional scaling (ordination) and cluster analysis packages. Although there exist a few resemblance functions that allow missing scores, is no theoretical background software support most distance similarity coefficients potentially applied in multivariate analysis. We provide general fr...

We study fundamental clustering problems for incomplete data. Specifically, given a set of d-dimensional vectors (representing rows matrix), the goal is to complete missing vector entries in way that admits partitioning into at most k clusters with radius or diameter r. give tight characterizations parameterized complexity these respect parameters k, r, and minimum number columns needed cover a...