Asymptotic theory of semiparametric \(Z\)-estimators for stochastic processes with applications to ergodic diffusions and time series

DOI10.1214/09-AOS693zbMath1369.62045arXiv0909.0439MaRDI QIDQ1043751

Yoichi Nishiyama

Publication date: 9 December 2009

Published in: The Annals of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/0909.0439

zbMATH Keywords

asymptotic efficiencynuisance parametermetric entropyestimating functiondiscrete observationergodic diffusion

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Central limit and other weak theorems (60F05) Markov processes: estimation; hidden Markov models (62M05)

Related Items (max. 100)

\(Z\)-process method for change point problems with applications to discretely observed diffusion processes ⋮ Asymptotically distribution free test for parameter change in a diffusion process model ⋮ Uniform and \(L_p\) convergences for nonparametric continuous time regressions with semiparametric applications ⋮ Variable bandwidth local maximum likelihood type estimation for diffusion processes ⋮ On \(Z\)-estimation by rounded data

Cites Work

• Unnamed Item
• Unnamed Item
• Estimation for diffusion processes from discrete observation
• Some central limit theorems for \(\ell^\infty\)-valued semimartingales and their applications
• Statistical inference for ergodic diffusion processes.
• Asymptotic theory of statistical inference for time series
• Weak convergence of some classes of martingales with jumps.
• Weak convergence and empirical processes. With applications to statistics
• A maximal inequality for continuous martingales and \(M\)-estimation in a Gaussian white noise model
• On the paper ``Weak convergence of some classes of martingales with jumps
• Introduction to empirical processes and semiparametric inference
• Donsker theorems for diffusions: necessary and sufficient conditions
• Approximate discrete-time schemes for statistics of diffusion processes
• Asymptotic Statistics
• Estimation of an Ergodic Diffusion from Discrete Observations
• On estimating the diffusion coefficient: Parametric versus nonparametric.

This page was built for publication: Asymptotic theory of semiparametric \(Z\)-estimators for stochastic processes with applications to ergodic diffusions and time series