The Bahadur representation for sample quantiles under strongly mixing sequence
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Publication:607174
DOI10.1016/j.jspi.2010.07.008zbMath1209.62116OpenAlexW2073168756MaRDI QIDQ607174
Shuhe Hu, Wenzhi Yang, Xue-jun Wang
Publication date: 19 November 2010
Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.jspi.2010.07.008
Related Items (13)
MODERATE DEVIATION PRINCIPLE OF SAMPLE QUANTILES AND ORDER STATISTICS ⋮ Assessing and Visualizing Simultaneous Simulation Error ⋮ On the Bahadur representation of sample quantiles for ψ-mixing sequences and its application ⋮ Asymptotics for the linear kernel quantile estimator ⋮ Modeling long term return distribution and nonparametric market risk estimation ⋮ Pointwise and uniform convergence of kernel density estimators using random bandwidths ⋮ The Berry-Esséen type bound of sample quantiles for strong mixing sequence ⋮ Markov chain Monte Carlo estimation of quantiles ⋮ Bahadur Representation of Linear Kernel Quantile Estimator for Stationary Processes ⋮ The Bahadur representation for sample quantiles under dependent sequence ⋮ The Bahadur representation of sample quantiles for weakly dependent sequences ⋮ On Bahadur representation for sample quantiles under \(\alpha\)-mixing sequence ⋮ The Bahadur representation of sample quantiles for φ-mixing random variables and its application
Cites Work
- On deviations between empirical and quantile processes for mixing random variables
- Nonparametric statistics for stochastic processes. Estimation and prediction.
- Smooth estimate of quantiles under association
- The Bahadur representation of sample quantiles for sequences of strongly mixing random variables
- The Bahadur representation for sample quantiles under weak dependence
- On the Bahadur representation of sample quantiles for dependent sequences
- On the Strong Law of Large Numbers and Related Results for Quasi-Stationary Sequences
- A Note on Quantiles in Large Samples
- Unnamed Item
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