Distributed testing on mutual independence of massive multivariate data

The article considers a distributed divide-and-conquer method to test the mutual independence between components of massive multivariate data. In particular, a new test statistic based on U-statistics by dividing the full data samples into disjoint blocks will be established. Some numerical simulations and real data analysis demonstrate that the proposed method is effective, and it can significantly reduce the computational complexity and save the running time of the test procedure on massive data inference.