A deterministic approach to survival statistics

Survival functions of the form p(t) = exp[−(λt)γ], γ > 0 can be generated by deterministic nonlinear, asymptotically stable (chaotic) dynamical systems. These systems thus provide an alternative to stochastic interpretations of failure time data. We use this approach to analyze cancer patient survival statistics. In this manner we are able to obtain fresh insights into the implications of negative and positive clinical trials.

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