scholarly journals Least squares estimation for non-ergodic weighted fractional Ornstein-Uhlenbeck process of general parameters

2021 ◽  
Vol 6 (11) ◽  
pp. 12780-12794
Author(s):  
Abdulaziz Alsenafi ◽  
◽  
Mishari Al-Foraih ◽  
Khalifa Es-Sebaiy

<abstract><p>Let $ B^{a, b}: = \{B_t^{a, b}, t\geq0\} $ be a weighted fractional Brownian motion of parameters $ a &gt; -1 $, $ |b| &lt; 1 $, $ |b| &lt; a+1 $. We consider a least square-type method to estimate the drift parameter $ \theta &gt; 0 $ of the weighted fractional Ornstein-Uhlenbeck process $ X: = \{X_t, t\geq0\} $ defined by $ X_0 = 0; \ dX_t = \theta X_tdt+dB_t^{a, b} $. In this work, we provide least squares-type estimators for $ \theta $ based continuous-time and discrete-time observations of $ X $. The strong consistency and the asymptotic behavior in distribution of the estimators are studied for all $ (a, b) $ such that $ a &gt; -1 $, $ |b| &lt; 1 $, $ |b| &lt; a+1 $. Here we extend the results of <sup>[<xref ref-type="bibr" rid="b1">1</xref>,<xref ref-type="bibr" rid="b2">2</xref>]</sup> (resp. <sup>[<xref ref-type="bibr" rid="b3">3</xref>]</sup>), where the strong consistency and the asymptotic distribution of the estimators are proved for $ -\frac12 &lt; a &lt; 0 $, $ -a &lt; b &lt; a+1 $ (resp. $ -1 &lt; a &lt; 0 $, $ -a &lt; b &lt; a+1 $). Simulations are performed to illustrate the theoretical results.</p></abstract>

Mathematics ◽  
2020 ◽  
Vol 8 (5) ◽  
pp. 716 ◽  
Author(s):  
Pavel Kříž ◽  
Leszek Szała

We introduce three new estimators of the drift parameter of a fractional Ornstein–Uhlenbeck process. These estimators are based on modifications of the least-squares procedure utilizing the explicit formula for the process and covariance structure of a fractional Brownian motion. We demonstrate their advantageous properties in the setting of discrete-time observations with fixed mesh size, where they outperform the existing estimators. Numerical experiments by Monte Carlo simulations are conducted to confirm and illustrate theoretical findings. New estimation techniques can improve calibration of models in the form of linear stochastic differential equations driven by a fractional Brownian motion, which are used in diverse fields such as biology, neuroscience, finance and many others.


2019 ◽  
Vol 20 (04) ◽  
pp. 2050023 ◽  
Author(s):  
Yong Chen ◽  
Nenghui Kuang ◽  
Ying Li

For an Ornstein–Uhlenbeck process driven by fractional Brownian motion with Hurst index [Formula: see text], we show the Berry–Esséen bound of the least squares estimator of the drift parameter based on the continuous-time observation. We use an approach based on Malliavin calculus given by Kim and Park [Optimal Berry–Esséen bound for statistical estimations and its application to SPDE, J. Multivariate Anal. 155 (2017) 284–304].


2019 ◽  
Vol 20 (02) ◽  
pp. 2050011 ◽  
Author(s):  
Fares Alazemi ◽  
Abdulaziz Alsenafi ◽  
Khalifa Es-Sebaiy

We consider a least square-type method to estimate the drift parameters for the mean-reverting Ornstein–Uhlenbeck process of the second kind [Formula: see text] defined as [Formula: see text], with unknown parameters [Formula: see text] and [Formula: see text], where [Formula: see text] with [Formula: see text], and [Formula: see text] is a Gaussian process. In order to establish the consistency and the asymptotic distribution of least square-type estimators of [Formula: see text] and [Formula: see text] based on the continuous-time observations [Formula: see text] as [Formula: see text], we impose some technical conditions on the process [Formula: see text], which are satisfied, for instance, if [Formula: see text] is a fractional Brownian motion with Hurst parameter [Formula: see text], [Formula: see text] is a subfractional Brownian motion with Hurst parameter [Formula: see text] or [Formula: see text] is a bifractional Brownian motion with Hurst parameters [Formula: see text]. Our method is based on pathwise properties of [Formula: see text] and [Formula: see text] proved in the sequel.


1995 ◽  
Vol 45 (3-4) ◽  
pp. 245-252 ◽  
Author(s):  
J. P. N. Bishwal ◽  
Arup Bose

Berry-Bsseen bounds with random norming and Jario deviation probabilities arc derived for the maximum likelihood estimator of the drift parameter in tho Ornstoin-Uhlenbeck proccss. AMS (1991) Subject Classification: Primary 62F12, 62M05 Secondary 60FOS, 60F10


2012 ◽  
Vol 2012 ◽  
pp. 1-9 ◽  
Author(s):  
Guangbin Wang ◽  
Yanli Du ◽  
Fuping Tan

We present preconditioned generalized accelerated overrelaxation methods for solving weighted linear least square problems. We compare the spectral radii of the iteration matrices of the preconditioned and the original methods. The comparison results show that the preconditioned GAOR methods converge faster than the GAOR method whenever the GAOR method is convergent. Finally, we give a numerical example to confirm our theoretical results.


2017 ◽  
Vol 11 (1) ◽  
pp. 385-400 ◽  
Author(s):  
Alexander Kukush ◽  
Yuliya Mishura ◽  
Kostiantyn Ralchenko

2019 ◽  
Vol 64 (3) ◽  
pp. 502-525
Author(s):  
Farez Alazemi ◽  
Farez Alazemi ◽  
Soukhana Douissi ◽  
Soukhana Douissi ◽  
Khalifa Es-Sebaiy ◽  
...  

Рассматривается задача оценивания сноса смешанного процесса Орнштейна-Уленбека на основе наблюдений в фиксированные дискретные моменты времени. С использованием исчисления Маллявена и недавнего анализа Нурдина-Пеккати исследуется асимптотическое поведение оценки. Более точно, изучаются сильная состоятельность и асимптотическое распределение оценки; установлена также скорость ее сходимости по распределению для всех $H\in(0,1)$. Более того, доказано, что в случае $H\in(0,3/4]$ оценка удовлетворяет центральной предельной теореме для сходимости почти наверное.


2013 ◽  
Vol 13 (03) ◽  
pp. 1250025 ◽  
Author(s):  
ALEXANDRE BROUSTE ◽  
CHUNHAO CAI

This paper is devoted to the determination of the asymptotical optimal input for the estimation of the drift parameter in a partially observed but controlled fractional Ornstein–Uhlenbeck process. Large sample asymptotical properties of the Maximum Likelihood Estimator are deduced using Ibragimov–Khasminskii program and Laplace transform computations.


2016 ◽  
Vol 48 (4) ◽  
pp. 989-1014 ◽  
Author(s):  
Gugan C. Thoppe ◽  
D. Yogeshwaran ◽  
Robert J. Adler

AbstractWe consider a time varying analogue of the Erdős–Rényi graph and study the topological variations of its associated clique complex. The dynamics of the graph are stationary and are determined by the edges, which evolve independently as continuous-time Markov chains. Our main result is that when the edge inclusion probability is of the form p=nα, where n is the number of vertices and α∈(-1/k, -1/(k + 1)), then the process of the normalised kth Betti number of these dynamic clique complexes converges weakly to the Ornstein–Uhlenbeck process as n→∞.


Sign in / Sign up

Export Citation Format

Share Document