Volume 23, Issue 2 | Statistical Inference for Stochastic Processes

Statistical Inference for Stochastic Processes

An International Journal devoted to Time Series Analysis and the Statistics of Continuous Time Processes and Dynamical Systems

Publishing model:: Hybrid

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Volume 23, Issue 2

July 2020

Special Issue: Statistical Analysis of Systems, Driven by the Fractional Brownian Motion

Issue Editor:

Marina Kleptsyna

9 articles in this issue

Preface
Marina Kleptsyna
EditorialNotes 23 June 2020 Pages: 249 - 249
Parameter identification for the Hermite Ornstein–Uhlenbeck process
Obayda Assaad
Ciprian A. Tudor
OriginalPaper 07 June 2020 Pages: 251 - 270
Adaptive estimation of the stationary density of a stochastic differential equation driven by a fractional Brownian motion
Karine Bertin
Nicolas Klutchnikoff
Maylis Varvenne
OriginalPaper 13 June 2020 Pages: 271 - 300
Testing for the change of the mean-reverting parameter of an autoregressive model with stationary Gaussian noise
Alexandre Brouste
Chunhao Cai
Longmin Wang
OriginalPaper 09 June 2020 Pages: 301 - 318
An M-estimator for stochastic differential equations driven by fractional Brownian motion with small Hurst parameter
Kohei Chiba
OriginalPaper 09 May 2020 Pages: 319 - 353
Spot estimation for fractional Ornstein–Uhlenbeck stochastic volatility model: consistency and central limit theorem
Yaroslav Eumenius-Schulz
OriginalPaper 27 March 2020 Pages: 355 - 380
A minimal contrast estimator for the linear fractional stable motion
Mathias Mørck Ljungdahl
Mark Podolskij
OriginalPaper 03 June 2020 Pages: 381 - 413
Comparison of the LS-based estimators and the MLE for the fractional Ornstein–Uhlenbeck process
Katsuto Tanaka
OriginalPaper 21 May 2020 Pages: 415 - 434
Asymptotic expansion of the quadratic variation of a mixed fractional Brownian motion
Ciprian A. Tudor
Nakahiro Yoshida
OriginalPaper 08 July 2020 Pages: 435 - 463