Nonparametric estimation in null recurrent time series.

DOI10.1214/aos/1009210546zbMath1103.62335OpenAlexW2001953116MaRDI QIDQ1848865

Hans Arnfinn Karlsen, Dag Tjøstheim

Publication date: 14 November 2002

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

Full work available at URL: https://projecteuclid.org/euclid.aos/1009210546

zbMATH Keywords

nonparametric kernel estimatorsnull recurrent Markov chainNonstationary time series modelssplit chain

Mathematics Subject Classification ID

Density estimation (62G07) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Asymptotic properties of nonparametric inference (62G20) Markov processes: estimation; hidden Markov models (62M05)

Related Items (61)

Estimation of partial differential equations with applications in finance ⋮ Consistent estimation of a general nonparametric regression function in time series ⋮ Local composite quantile regression smoothing for Harris recurrent Markov processes ⋮ UNIFORM CONSISTENCY FOR NONPARAMETRIC ESTIMATORS IN NULL RECURRENT TIME SERIES ⋮ Robust estimation in a nonlinear cointegration model ⋮ ASYMPTOTIC THEORY FOR LOCAL TIME DENSITY ESTIMATION AND NONPARAMETRIC COINTEGRATING REGRESSION ⋮ Kernel Density Estimation and Local Time ⋮ MARTINGALE LIMIT THEOREM REVISITED AND NONLINEAR COINTEGRATING REGRESSION ⋮ LOCAL LINEAR FITTING UNDER NEAR EPOCH DEPENDENCE ⋮ Adaptive estimation for varying coefficient models with nonstationary covariates ⋮ Specification testing for nonlinear multivariate cointegrating regressions ⋮ SPECIFICATION TESTING DRIVEN BY ORTHOGONAL SERIES FOR NONLINEAR COINTEGRATION WITH ENDOGENEITY ⋮ Inference in nonstationary asymmetric GARCH models ⋮ Nonparametric LAD cointegrating regression ⋮ Threshold models in time series analysis -- some reflections ⋮ NULL RECURRENT UNIT ROOT PROCESSES ⋮ Nonparametric prediction of stock returns based on yearly data: the long-term view ⋮ Testing of Constant Parameters for Semi‐Parametric Functional Coefficient Models with Integrated Covariates ⋮ Extreme values statistics for Markov chains via the (pseudo-) regenerative method ⋮ Estimation in semi-parametric regression with non-stationary regressors ⋮ Nonparametric estimation of a scalar diffusion model from discrete time data: a survey ⋮ Asymptotic theory for fractional regression models via Malliavin calculus ⋮ Buffered vector error-correction models: an application to the U.S. Treasury bond rates ⋮ A specification test for nonlinear nonstationary models ⋮ Semiparametric estimation in triangular system equations with nonstationarity ⋮ When is a Markov chain regenerative? ⋮ Uniform convergence rates for a class of martingales with application in non-linear cointegrating regression ⋮ On non-parametric estimation of the Lévy kernel of Markov processes ⋮ ADAPTIVE TESTING IN CONTINUOUS-TIME DIFFUSION MODELS ⋮ Monte Carlo methods for improper target distributions ⋮ Robust nonlinear regression estimation in null recurrent time series ⋮ Varying coefficient partially nonlinear models with nonstationary regressors ⋮ Estimation in threshold autoregressive models with a stationary and a unit root regime ⋮ NONPARAMETRIC COINTEGRATING REGRESSION WITH NNH ERRORS ⋮ Asymptotic behavior for bi-fractional regression models via Malliavin calculus ⋮ UNIFORM CONSISTENCY OF NONSTATIONARY KERNEL-WEIGHTED SAMPLE COVARIANCES FOR NONPARAMETRIC REGRESSION ⋮ Nonparametric methods of inference for finite-state, inhomogeneous Markov processes ⋮ NONPARAMETRIC TRANSFORMATION REGRESSION WITH NONSTATIONARY DATA ⋮ A weighted sieve estimator for nonparametric time series models with nonstationary variables ⋮ Nonparametric regression estimation in a null recurrent time series ⋮ Estimation of integrals with respect to infinite measures using regenerative sequences ⋮ ON THE FUNCTIONAL ESTIMATION OF MULTIVARIATE DIFFUSION PROCESSES ⋮ Nonparametric estimation in a nonlinear cointegration type model ⋮ Estimation for single-index and partially linear single-index integrated models ⋮ Bandwidth selection and asymptotic properties of local nonparametric estimators in possibly nonstationary continuous-time models ⋮ Estimation and inference in the presence of fractional \(d=1/2\) and weakly nonstationary processes ⋮ Estimation of dynamic models with nonparametric simulated maximum likelihood ⋮ Approximate regenerative-block bootstrap for Markov chains ⋮ NONPARAMETRIC NONSTATIONARITY TESTS ⋮ Empirical process theory for locally stationary processes ⋮ NONPARAMETRIC SPECIFICATION TESTING FOR NONLINEAR TIME SERIES WITH NONSTATIONARITY ⋮ Nearest neighbor conditional estimation for Harris recurrent Markov chains ⋮ Specification testing in nonlinear and nonstationary time series autoregression ⋮ Regeneration-based statistics for Harris recurrent Markov chains ⋮ Bootstrapping Robust Statistics for Markovian Data Applications to Regenerative R‐Statistics and L‐Statistics ⋮ Nonparametric estimation in null recurrent time series. ⋮ Expansion and estimation of Lévy process functionals in nonlinear and nonstationary time series regression ⋮ Some notes on nonlinear cointegration: A partial review with some novel perspectives ⋮ Nonlinear regressions with nonstationary time series ⋮ A uniform law for convergence to the local times of linear fractional stable motions ⋮ NONSTATIONARY NONLINEARITY: A SURVEY ON PETER PHILLIPS’S CONTRIBUTIONS WITH A NEW PERSPECTIVE

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Limit theorems for Lévy processes and Poisson point processes and their applications to Brownian excursions
• Nonparametric estimation in a nonlinear cointegration type model
• A limit theorem for sums of random number of i.i.d. random variables and its application to occupation times of Markov chains
• A limit theorem for slowly increasing occupation times
• Linearity testing using local polynomial approximation
• Nearest neighbor regression estimation for null-recurrent Markov time series
• Computable bounds for geometric convergence rates of Markov chains
• Large-sample inference for nonparametric regression with dependent errors
• Local asymptotic normality and mixed normality for Markov statistical models
• Nonparametric estimation in null recurrent time series.
• The sequence of sums of independent random variables
• Distribution of the Estimators for Autoregressive Time Series With a Unit Root
• NULL RECURRENT UNIT ROOT PROCESSES
• On Occupation Times for Markoff Processes
• NONPARAMETRIC ESTIMATORS FOR TIME SERIES
• General Irreducible Markov Chains and Non-Negative Operators
• Nonparametric Estimation and Identification of Nonlinear ARCH Time Series Strong Convergence and Asymptotic Normality: Strong Convergence and Asymptotic Normality
• RANDOM COEFFICIENT AUTOREGRESSIVE PROCESSES:A MARKOV CHAIN ANALYSIS OF STATIONARITY AND FINITENESS OF MOMENTS
• Likelihood-Based Inference in Cointegrated Vector Autoregressive Models
• Nonparametric Identification of Nonlinear Time Series: Projections
• Modelling Nonlinear Relationships between Extended-Memory Variables
• NONLINEAR TRANSFORMATIONS OF INTEGRATED TIME SERIES
• Convergence of stochastic processes

This page was built for publication: Nonparametric estimation in null recurrent time series.