Parameter estimation for fractional Ornstein–Uhlenbeck processes of general Hurst parameter
نویسندگان
چکیده
منابع مشابه
Estimation of the Hurst parameter in some fractional processes
We propose to estimate the Hurst parameter involved in fractional processes via a method based on the Karhunen-Loève expansion of Gaussian process.We specifically investigate the cases of the Fractional Brownian motion(FBm) and the Fractional Ornstein-Uhlenbeck(FOU) Family. The main tool is the analysis of the residuals of a convenient linear regression model. We numerically compare our results...
متن کاملParameter Estimation for Fractional Poisson Processes
The paper proposes a formal estimation procedure for parameters of the fractional Poisson process (fPp). Such procedures are needed to make the fPp model usable in applied situations. The basic idea of fPp, motivated by experimental data with long memory is to make the standard Poisson model more flexible by permitting nonexponential, heavy-tailed distributions of interarrival times and differe...
متن کاملParameter estimation for fractional Ornstein-Uhlenbeck processes
We study a least squares estimator b θT for the Ornstein-Uhlenbeck process, dXt = θXtdt+σdB H t , driven by fractional Brownian motion B H with Hurst parameter H ≥ 1 2 . We prove the strong consistence of b θT (the almost surely convergence of b θT to the true parameter θ). We also obtain the rate of this convergence when 1/2 ≤ H < 3/4, applying a central limit theorem for multiple Wiener integ...
متن کاملHurst Parameter Estimation for Epileptic Seizure Detection
Estimation of the Hurst parameter provides information about the memory range or correlations (long vs. short) of processes (time-series). A new application for the Hurst parameter, real-time event detection, is identified. Hurst estimates using rescaled range, dispersional and bridgedetrended scaled windowed variance analyses of seizure time-series recorded from human subjects reliably detect ...
متن کاملHurst Parameter Estimation Using Artificial Neural Networks
The Hurst parameter captures the amount of long-range dependence (LRD) in a time series. There are several methods to estimate the Hurst parameter, being the most popular: the variance-time plot, the R/S plot, the periodogram, and Whittle’s estimator. The first three are graphical methods, and the estimation accuracy depends on how the plot is interpreted and calculated. In contrast, Whittle’s ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Statistical Inference for Stochastic Processes
سال: 2017
ISSN: 1387-0874,1572-9311
DOI: 10.1007/s11203-017-9168-2