  The rapid development of modern technology facilitates the appearance of
numerous unprecedented complex data which do not satisfy the axioms of
Euclidean geometry, while most of the statistical hypothesis tests are
available in Euclidean or Hilbert spaces. To properly analyze the data of more
complicated structures, efforts have been made to solve the fundamental test
problems in more general spaces. In this paper, a publicly available R package
Ball is provided to implement Ball statistical test procedures for K-sample
distribution comparison and test of mutual independence in metric spaces, which
extend the test procedures for two sample distribution comparison and test of
independence. The tailormade algorithms as well as engineering techniques are
employed on the Ball package to speed up computation to the best of our
ability. Two real data analyses and several numerical studies have been
performed and the results certify the powerfulness of Ball package in analyzing
complex data, e.g., spherical data and symmetric positive matrix data.
