The telegraph process X(t), t ≥ 0, (Goldstein, Q J Mech Appl Math 4:129-156, 1951) and the geometric telegraph process S(t) = s0 exp{μ -1/2σ2)t + σ X(t)}with μ a known real constant and σ > 0 a parameter are supposed to be observed at n + 1 equidistant time points t i = iΔ n ,i = 0,1,..., n. For both models λ, the underlying rate of the Poisson process, is a parameter to be estimated. In the geometric case, also σ > 0 has to be estimated. We propose different estimators of the parameters and we investigate their performance under the asymptotics, i.e. Δ n → 0, nΔ n = T < ∞ as n → ∞, with T > 0 fixed. The process X(t) in non markovian, non stationary and not ergodic thus we build a contrast function to derive an estimator. Given the complexity of the equations involved only estimators on the first model can be studied analytically. Therefore, we run an extensive Monte Carlo analysis to study the performance of the proposed estimators also for small sample size n. © 2007 Springer Science+Business Media B.V.

Parametric estimation for the standard and geometric telegraph process observed at discrete times / DE GREGORIO, Alessandro; Stefano Maria, Iacus. - In: STATISTICAL INFERENCE FOR STOCHASTIC PROCESSES. - ISSN 1387-0874. - 11:3(2008), pp. 249-263. [10.1007/s11203-007-9017-9]

Parametric estimation for the standard and geometric telegraph process observed at discrete times

DE GREGORIO, ALESSANDRO;
2008

Abstract

The telegraph process X(t), t ≥ 0, (Goldstein, Q J Mech Appl Math 4:129-156, 1951) and the geometric telegraph process S(t) = s0 exp{μ -1/2σ2)t + σ X(t)}with μ a known real constant and σ > 0 a parameter are supposed to be observed at n + 1 equidistant time points t i = iΔ n ,i = 0,1,..., n. For both models λ, the underlying rate of the Poisson process, is a parameter to be estimated. In the geometric case, also σ > 0 has to be estimated. We propose different estimators of the parameters and we investigate their performance under the asymptotics, i.e. Δ n → 0, nΔ n = T < ∞ as n → ∞, with T > 0 fixed. The process X(t) in non markovian, non stationary and not ergodic thus we build a contrast function to derive an estimator. Given the complexity of the equations involved only estimators on the first model can be studied analytically. Therefore, we run an extensive Monte Carlo analysis to study the performance of the proposed estimators also for small sample size n. © 2007 Springer Science+Business Media B.V.
2008
discretely observed process; inference for stochastic processes; telegraph process
01 Pubblicazione su rivista::01a Articolo in rivista
Parametric estimation for the standard and geometric telegraph process observed at discrete times / DE GREGORIO, Alessandro; Stefano Maria, Iacus. - In: STATISTICAL INFERENCE FOR STOCHASTIC PROCESSES. - ISSN 1387-0874. - 11:3(2008), pp. 249-263. [10.1007/s11203-007-9017-9]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/140253
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