Cheng-Shang Chang, Randolph Nelson, et al.
Performance Evaluation
Chemoff’s bound on P[X ≥ t] is used almost universally when a tight bound on tail probabilities is required. In this article we show that for all positive t and for all distributions, the moment bound is tighter than Chemoff’s bound. By way of example, we demonstrate that the improvement is often substantial. © Taylor & Francis Group, LLC.
Cheng-Shang Chang, Randolph Nelson, et al.
Performance Evaluation
Randolph Nelson, Leonard Kleinrock
IEEE Transactions on Communications
Randolph D. Nelson, Thomas K. Philips
Performance Evaluation
Randolph Nelson
Journal of the ACM