Asymptotics of Quantiles and Rank Scores in Nonlinear Time Series

DOI10.1111/1467-9892.00132zbMath0938.62101OpenAlexW1984584489MaRDI QIDQ4956027

Kanchan Mukherjee

Publication date: 24 May 2000

Published in: Journal of Time Series Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/1467-9892.00132

zbMATH Keywords

regression quantilesL-estimatorsnonlinear time seriesrobust estimationautoregression quantilesself-exciting threshold autoregressive modelsheavy-tailed error distributionsrank scores

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) General nonlinear regression (62J02)

Related Items (10)

Dynamic quantile models ⋮ Self-Weighted Least Absolute Deviation Estimation for Infinite Variance Autoregressive Models ⋮ Asymptotics of the signed-rank estimator under dependent observations ⋮ The signed-rank estimator for nonlinear regression with responses missing at random ⋮ A dynamic autoregressive expectile for time-invariant portfolio protection strategies ⋮ ASYMPTOTIC THEORY FOR NONLINEAR QUANTILE REGRESSION UNDER WEAK DEPENDENCE ⋮ Specification tests of parametric dynamic conditional quantiles ⋮ Signed-rank regression inference via empirical likelihood ⋮ Nonstationary nonlinear quantile regression ⋮ Testing for Granger-causality in quantiles

This page was built for publication: Asymptotics of Quantiles and Rank Scores in Nonlinear Time Series