The asymptotic distribution of nonparametric estimates of the Lyapunov exponent for stochastic time series

DOI10.1016/S0304-4076(98)00047-5zbMath1041.62503OpenAlexW2068932957WikidataQ127212406 ScholiaQ127212406MaRDI QIDQ1298473

Yoon-Jae Whang, Oliver B. Linton

Publication date: 1999

Published in: Journal of Econometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0304-4076(98)00047-5

zbMATH Keywords

Nonparametric regressionChaosNonlinear dynamicsKernelSemiparametric

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Parametric tolerance and confidence regions (62F25) Asymptotic distribution theory in statistics (62E20)

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Uses Software

• nlmdl

Cites Work

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• Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation
• A functional central limit theorem for weakly dependent sequences of random variables
• Extremal theory for stochastic processes
• An algorithm for the \(n\) Lyapunov exponents of an \(n\)-dimensional unknown dynamical system
• Mixing: Properties and examples
• Distinguishing random and deterministic systems: Abridged version
• A statistical framework for testing chaotic dynamics via Lyapunov exponents
• Sur la distribution limite du terme maximum d'une série aléatoire
• NONPARAMETRIC ESTIMATORS FOR TIME SERIES
• Investigating Smooth Multiple Regression by the Method of Average Derivatives
• A Simple, Positive Semi-Definite, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix
• An Improved Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimator
• Consistent Covariance Matrix Estimation for Dependent Heterogeneous Processes
• Estimating the Lyapunov Exponent of a Chaotic System With Nonparametric Regression
• Bandwidth Choice for Average Derivative Estimation
• Asymptotics for Semiparametric Econometric Models Via Stochastic Equicontinuity
• The Asymptotic Variance of Semiparametric Estimators
• MULTIVARIATE LOCAL POLYNOMIAL REGRESSION FOR TIME SERIES:UNIFORM STRONG CONSISTENCY AND RATES
• Nonparametric regression estimation at design poles and zeros
• Products of Random Matrices
• Extreme Values in Uniformly Mixing Stationary Stochastic Processes
• Extreme Values in Samples from $m$-Dependent Stationary Stochastic Processes