首页 | 本学科首页   官方微博 | 高级检索  
     检索      


Parametric estimation for the standard and geometric telegraph process observed at discrete times
Authors:Alessandro De Gregorio  Stefano Maria Iacus
Institution:(1) Department of Economics, Business and Statistics, University of Milan, Via Conservatorio 7, 20122 Milan, Italy
Abstract:The telegraph process X(t), t ≥ 0, (Goldstein, Q J Mech Appl Math 4:129–156, 1951) and the geometric telegraph process $$S(t) = s_{0} {\rm exp}\{(\mu -\frac12\sigma^{2})t + \sigma X(t)\}$$ 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.
Keywords:Telegraph process  Discretely observed process  Inference for stochastic processes
本文献已被 SpringerLink 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号