Estimation–Calibration of Continuous-Time Non-Homogeneous Markov Chains with Finite State Space

Esquível, Manuel L.; Krasii, Nadezhda Pavlovna; Guerreiro, Gracinda R.

http://hdl.handle.net/10362/179069

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Autores

Esquível, Manuel L.

Krasii, Nadezhda Pavlovna

Guerreiro, Gracinda R.

Resumo(s)

We propose a method for fitting transition intensities to a sufficiently large set of trajectories of a continuous-time non-homogeneous Markov chain with a finite state space. Starting with simulated data computed with Gompertz–Makeham transition intensities, we apply the proposed method to fit piecewise linear intensities and then compare the transition probabilities corresponding to both the Gompertz–Makeham transition intensities and the fitted piecewise linear intensities; the main comparison result is that the order of magnitude of the average fitting error per unit time—chosen as a year—is always less than 1%, thus validating the methodology proposed.

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calibration continuous time estimation health insurance long-term care Markov chains non homogeneous regime switching processes Computer Science (miscellaneous) General Mathematics Engineering (miscellaneous)