An algorithm is considered for including, and excluding the arguments of ti
me and random events in an autocorrelation function by means of a set of (0
, 1) coefficients. Conclusions are drawn oil the optimality of classical au
tocorrelation function relations and oil the isomorphism of the probability
of overlooking errors corresponding to the method of identifying an asympt
otic set with ordinary and conditional probabilities.