The Bahadur representation of sample quantiles for sequences of strongly mixing random variables
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Publication:1903177
DOI10.1016/0167-7152(94)00187-DzbMath0835.62048OpenAlexW1969979045MaRDI QIDQ1903177
Publication date: 26 November 1995
Published in: Statistics \& Probability Letters (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/0167-7152(94)00187-d
Asymptotic properties of nonparametric inference (62G20) Order statistics; empirical distribution functions (62G30) Strong limit theorems (60F15)
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Assessing and Visualizing Simultaneous Simulation Error ⋮ Strong Approximation of Quantile Function for Strong Mixing and Censored Processes ⋮ On the Bahadur representation of sample quantiles for ψ-mixing sequences and its application ⋮ Berry-Esséen bound of sample quantiles for negatively associated sequence ⋮ The Bahadur representation for sample quantiles under strongly mixing sequence ⋮ Sample quantile analysis for long-memory stochastic volatility models ⋮ Simulating risk measures via asymptotic expansions for relative errors ⋮ Some improved results on Berry–Esséen bounds for strong mixing random variables and applications ⋮ A remark on the Bahadur representation of sample quantiles for negatively associated sequences ⋮ Normal limits, nonnormal limits, and the bootstrap for quantiles of dependent data ⋮ Sequest: A Sequential Procedure for Estimating Quantiles in Steady-State Simulations ⋮ The Berry-Esséen type bound of sample quantiles for strong mixing sequence ⋮ Hurst exponent estimation of locally self-similar Gaussian processes using sample quantiles ⋮ Bahadur representation of sample quantiles for a functional of Gaussian dependent sequences under a minimal assumption ⋮ The Bahadur representation for sample quantiles under negatively associated sequence ⋮ Testing Independence in Linear Process with Non-Normal Innovations ⋮ Rank tests for short memory stationarity ⋮ Strong Gaussian approximations of product-limit and quantile processes for truncated data under strong mixing ⋮ Bahadur representation of linear kernel quantile estimator of VaR under \(\alpha \)-mixing assumptions ⋮ Bahadur representation for \(U\)-quantiles of dependent data ⋮ Strong Gaussian Approximations of Product-Limit and Quantile Processes for Strong Mixing and Censored Data ⋮ Bahadur Representation of Linear Kernel Quantile Estimator for Stationary Processes ⋮ The Bahadur representation for kernel-type estimator of the quantile function under strong mixing and censored data ⋮ The Bahadur representation for sample quantiles under weak dependence ⋮ The Bahadur representation for sample quantiles under dependent sequence ⋮ A note on bias and mean squared error in steady-state quantile estimation ⋮ Inference for performance measures for financial assets ⋮ The Bahadur representation of sample quantiles for weakly dependent sequences ⋮ On Bahadur representation for sample quantiles under \(\alpha\)-mixing sequence ⋮ A note on the Bahadur representation of sample quantiles for \(\alpha \)-mixing random variables ⋮ The Bahadur representation of sample quantiles for φ-mixing random variables and its application ⋮ Set-indexed conditional empirical and quantile processes based on dependent data ⋮ Multivariate generalized linear-statistics of short range dependent data
Cites Work
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- A general moment inequality for the maximum of the rectangular partial sums of multiple series
- On deviations between empirical and quantile processes for mixing random variables
- Weak convergence of multidimensional empirical processes for strong mixing sequences of stochastic vectors
- A Note on Quantiles in Large Samples
- Extensions of Billingsley's theorems on weak convergence of empirical processes
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