  The statistical method is used to identify the hidden leaders of the
corruption structure. The method is based on principal component analysis
(PCA), linear regression, and Shannon information. It is applied to study the
time series data of corrupt financial activity.
  Shannon's quantity of information is specified as a function of two
arguments: a vector of hidden corruption factors and a subset of corrupt
agents. Several optimization problems are solved to determine the contribution
of corresponding corrupt agents to the total illegal behavior. An illustrative
example is given. A convenient algorithm for computing the covariance matrix
with missing data is proposed.
