Random factor analysis is a statistical technique to decipher whether outlying data is caused by an underlying trend or just simply a random event.

A rich and flexible class of random probability measures, which we call stick-breaking priors, can be constructed using a sequence of independent beta random variables. Examples of random measures ...

David Gilat, Some Conditions Under Which Two Random Variables are Equal Almost Surely and a Simple Proof of a Theorem of Chung and Fuchs, The Annals of Mathematical Statistics, Vol. 42, No. 5 (Oct., ...