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In this article, we use the first-passage-time theory for a stochastic process to formulate a dynamic model expressing the human life table data. The model is derived analytically by using the corresponding Laplace transforms for the probability density function of the stochastic process and then the theory for the hitting time process is used to derive the probability density function for the first exit time. The tangent approximation to one-sided Brownian exit densities is used. The resulting probability density function is applied to mortality data. The stochastic simulation is using the Health State Function proposed with encouraging results.
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Papers that cite the same references — the relational fallback while embeddings are still backfilling.
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