Parametric estimation in the Vasicek-type model driven by sub-fractional Brownian motion
type: Item
instance of: scholarly article
title: Parametric estimation in the Vasicek-type model driven by sub-fractional Brownian motion
zbMATH Open document ID: 1461.62149
author: Shengfeng Li
author: Yi Dong
published in: Algorithms
publication date: 2019-01-21T00:00:00Z
review text: Summary: In the paper, we tackle the least squares estimators of the Vasicek-type model driven by sub-fractional Brownian motion: \[ d X_t = (\mu + \theta X_t) d t + d S_t^H,\quad t \geq 0 \] with \(X_0 = 0\), where \(S^H\) is a sub-fractional Brownian motion whose Hurst index \(H\) is greater than \(\frac{1}{2}\), and \(\mu \in \mathbb R\), \(\theta \in \mathbb R^+\) are two unknown parameters. Based on the so-called continuous observations, we suggest the least square estimators of \(\mu\) and \(\theta\) and discuss the consistency and asymptotic distributions of the two estimators.
Mathematics Subject Classification ID: 62M05
Mathematics Subject Classification ID: 60G22
Mathematics Subject Classification ID: 60H05
Mathematics Subject Classification ID: 62F12
zbMATH DE Number: 7003848
zbMATH Keywords: least squares method
zbMATH Keywords: sub-fractional Brownian motion
zbMATH Keywords: Vasicek-type model
zbMATH Keywords: Young's integration
zbMATH Keywords: asymptotic distribution
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.3390/a11120197
OpenAlex ID: W2902820687
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Wikidata QID: Q128825772
DOI: 10.3390/A11120197
description: scientific article; zbMATH DE number 7003848