English

Nonparametric estimation of linear multiplier for processes driven by a Hermite process

Statistics Theory 2026-02-19 v1 Probability Statistics Theory

Abstract

We study the problem of nonparametric estimation of the linear multiplier function θ(t)\theta(t) for processes satisfying stochastic differential equations of the type dXt=θ(t)Xtdt+ϵdZtq,H,X0=x0,0tTdX_t=\theta(t) X_tdt+ \epsilon dZ^{q,H}_t, X_0=x_0, 0\leq t \leq T where {Ztq,H,t0}\{Z^{q,H}_t, t \geq 0\} is a Hermite process with known order qq and known self-similarity parameter H(12,1).H \in (\frac{1}{2},1). We investigate the asymptotic behaviour of the estimator of the unknown function θ(t)\theta(t) as ϵ0.\epsilon \rightarrow 0.

Cite

@article{arxiv.2602.16223,
  title  = {Nonparametric estimation of linear multiplier for processes driven by a Hermite process},
  author = {B. L. S. Prakasa Rao},
  journal= {arXiv preprint arXiv:2602.16223},
  year   = {2026}
}
R2 v1 2026-07-01T10:40:54.556Z