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This correspondence is concerned with binary processes and presents results with immediate applications in the modeling of digital channels for the purpose of evaluating code performance. It is demonstrated that cluster density can be analytically described from the distributions of intervals between errors. These relations and derived clustering properties hold for any stationary process. Analyses of real error data exemplify the use of these results in regard to channels having dependent inter-error intervals.