Nonparametric estimation for irregularly sampled Lévy processes
نویسندگان
چکیده
منابع مشابه
Nonparametric estimation for pure jump irregularly sampled or noisy Lévy processes
In this paper, we study nonparametric estimation of the Lévy density for pure jump Lévy processes. We consider n discrete time observations that may be irregularly sampled or possibly corrupted by a small noise independent of the main process. The case of non noisy observations with regular sampling interval has been studied by the authors in previous works which are the benchmark for the exten...
متن کاملNonparametric adaptive estimation for discretely observed Lévy processes
This thesis deals with nonparametric estimation methods for discretely observed Lévy processes. The following statistical framework is considered: A Lévy process X having finite variation on compact sets and finite second moments is observed at low frequency. In this situation, the jump dynamics is fully described by the finite signed measure μ(dx) = xν(dy). The goal is to estimate, nonparametr...
متن کاملNonparametric estimation of intensities for sampled counting processes
for the analysis of stationary time :;t;:,llt::;. studied We express some time reconas smoothed versions of corresponding point process parameters, and use these relations suggest estimates of series narameters
متن کاملFisher ’ S Information for Discretely Sampled Lévy Processes
This paper studies the asymptotic behavior of the Fisher information for a Lévy process discretely sampled at an increasing frequency. We show that it is possible to distinguish not only the continuous part of the process from its jumps part, but also different types of jumps, and derive the rates of convergence of efficient estimators.
متن کاملNonparametric Estimation for Stationary Processes
We consider the kernel density and regression estimation problem for a wide class of causal processes. Asymptotic normality of the kernel estimators is established under minimal regularity conditions on bandwidths. Optimal uniform error bounds are obtained without imposing strong mixing conditions. The proposed method is based on martingale approximations and provides a unified framework for no...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Statistical Inference for Stochastic Processes
سال: 2016
ISSN: 1387-0874,1572-9311
DOI: 10.1007/s11203-016-9144-2