Asymptotic inference in some heteroscedastic regression models with long memory design and errors

DOI10.1214/009053607000000686zbMath1132.62066arXiv0803.2121OpenAlexW2141676311MaRDI QIDQ2477069

Hira L. Koul, Hongwen Guo

Publication date: 12 March 2008

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

Full work available at URL: https://arxiv.org/abs/0803.2121

zbMATH Keywords

model diagnosticsOLSmoving average errorslocal whittle estimator

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Asymptotic distribution theory in statistics (62E20) Asymptotic properties of nonparametric inference (62G20) Applications of statistics to actuarial sciences and financial mathematics (62P05) Non-Markovian processes: estimation (62M09)

Related Items

Smooth Estimation of Error Distribution in Nonparametric Regression Under Long Memory, Conditional variance estimation in regression models with long memory, Comparing two nonparametric regression curves in the presence of long memory in covariates and errors, Wavelet deconvolution in a periodic setting with long-range dependent errors, Accounting for uncertainty in heteroscedasticity in nonlinear regression, Long-range dependent time series specification, Kink estimation in stochastic regression with dependent errors and predictors, Nonparametric conditional variance and error density estimation in regression models with dependent errors and predictors, Asymptotic behaviour of the LS estimator in a nonlinear model with long memory, Minimum distance lack-of-fit tests under long memory errors, Lack of fit test for long memory regression models, Wavelet regression in random design with heteroscedastic dependent errors

Uses Software

• longmemo

Cites Work

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