arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 1909.06155math.PRmath.STstat.TH
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非遍历Gaussian Vasicek型模型中漂移参数的估计

Estimating drift parameters in a non-ergodic Gaussian Vasicek-type model

Khalifa Es-Sebaiy, Mohammed Es. Sebaiy

摘要:

研究了一类非遍历Gaussian Vasicek型模型$dX_t=(μ+θX_t)dt+dG_t,\ t\geq0$的参数估计问题,其中参数$θ>0$和$μ\in\mathbb{R}$均为未知,其中$G$为高斯过程.基于连续时间观测值$\{X_t,\ t\in[0,T]\}$作为$T\rightarrow\infty$,分别给出了漂移参数$θ$和$μ$的最小二乘估计$\widetildeθ_T$和$\widetildeμ_T$.我们的目的是得到驱动高斯过程$G$的一些充分条件,以保证$\widetildeθ_T$和$\widetildeμ_T$是强相容的,$\widetildeθ_T$的极限分布是Cauchy型分布,$\widetildeμ_T$是渐近正态的.我们应用我们的结果分数Vasicek,亚分数Vasicek和bifractional Vasicek过程。此外,本文的工作推广了\cite{EEO}在$μ=0$ .

英文摘要:

We study the problem of parameter estimation for a non-ergodic Gaussian Vasicek-type model defined as $dX_t=(μ+θX_t)dt+dG_t,\ t\geq0$ with unknown parameters $θ>0$ and $μ\in\mathbb{R}$, where $G$ is a Gaussian process. We provide least square-type estimators $\widetildeθ_T$ and $\widetildeμ_T$ respectively for the drift parameters $θ$ and $μ$ based on continuous-time observations $\{X_t,\ t\in[0,T]\}$ as $T\rightarrow\infty$. Our aim is to derive some sufficient conditions on the driving Gaussian process $G$ in order to ensure that $\widetildeθ_T$ and $\widetildeμ_T$ are strongly consistent, the limit distribution of $\widetildeθ_T$ is a Cauchy-type distribution and $\widetildeμ_T$ is asymptotically normal. We apply our result to fractional Vasicek, subfractional Vasicek and bifractional Vasicek processes. In addition, this work extends the result of \cite{EEO} studied in the case where $μ=0$.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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