Bahadur Representation of Linear Kernel Quantile Estimator for Stationary Processes

DOI10.1080/03610926.2012.736582zbMath1322.60019OpenAlexW1963575374MaRDI QIDQ5177575

Unnamed Author, Zhang Lixin

Publication date: 13 March 2015

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610926.2012.736582

zbMATH Keywords

Bahadur representationalmost sure convergencestationary processeskernel quantile estimator\(S\)-mixing sequence

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Stationary stochastic processes (60G10) Strong limit theorems (60F15)

Related Items (2)

Asymptotics for the linear kernel quantile estimator ⋮ Retracted article: Jacobi spectral solution for integral algebraic equations of index 1

Cites Work

• The Bahadur representation for sample quantiles under strongly mixing sequence
• Bahadur representation of linear kernel quantile estimator of VaR under \(\alpha \)-mixing assumptions
• Asymptotic results for the empirical process of stationary sequences
• The Bahadur representation of sample quantiles for sequences of strongly mixing random variables
• Bahadur-Kiefer theory for sample quantiles of weakly dependent linear processes
• On the Bahadur representation of sample quantiles for dependent sequences
• A Note on Quantiles in Large Samples
• On Estimation of a Probability Density Function and Mode

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