Marked empirical processes for non-stationary time series

DOI10.3150/12-BEJ444zbMath1412.62115arXiv1312.3120OpenAlexW3098888453MaRDI QIDQ2435236

Ngai Hang Chan, Rong Mao Zhang

Publication date: 4 February 2014

Published in: Bernoulli (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1312.3120

zbMATH Keywords

quantile regressionunit rootgoodness-of-fitlong-memorymarked empirical process

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Nonparametric estimation (62G05) Central limit and other weak theorems (60F05) Functional limit theorems; invariance principles (60F17)

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Noncentral limit theorems and Appell polynomials
• Convergence in various topologies for stochastic integrals driven by semimartingales
• Lectures on empirical processes. Theory and statistical applications.
• Composite quantile regression and the oracle model selection theory
• Residual empirical processes for long and short memory time series
• Weak convergence of non-stationary multivariate marked processes with applications to martingale testing
• Quantile inference for near-integrated autoregressive time series under infinite variance and strong dependence
• Limit theory for the sample covariance and correlation functions of moving averages
• Weak limit theorems for stochastic integrals and stochastic differential equations
• Weak convergence of sums of moving averages in the \(\alpha\)-stable domain of attraction
• Approximating martingales and the central limit theorem for strictly stationary processes
• Random difference equations and renewal theory for products of random matrices
• A bivariate stable characterization and domains of attraction
• A non-Skorokhod topology on the Skorokhod space
• Empirical processes of long-memory sequences
• Stochastic integral equations without probability
• Limiting distributions of maximum likelihood estimators for unstable autoregressive moving-average time series with general autoregressive heteroscedastic errors
• On the asymptotic expansion of the empirical process of long-memory moving averages
• Long memory processes and fractional integration in econometrics
• Strong invariance principles for dependent random variables
• Fitting an error distribution in some heteroscedastic time series models
• The conditional central limit theorem in Hilbert spaces.
• An inequality of the Hölder type, connected with Stieltjes integration
• Long Memory in Economics
• ASYMPTOTIC DISTRIBUTION-FREE DIAGNOSTIC TESTS FOR HETEROSKEDASTIC TIME SERIES MODELS
• Model diagnosis for parametric regression in high-dimensional spaces
• Holder Conditions for Gaussian Processes with Stationary Increments
• Convergence Criteria for Multiparameter Stochastic Processes and Some Applications
• Goodness-of-Fit Tests for Linear and Nonlinear Time Series Models

This page was built for publication: Marked empirical processes for non-stationary time series