Kernel estimation of the density of a statistic

DOI10.1016/0167-7152(94)90055-8zbMath0801.62038OpenAlexW2038459153MaRDI QIDQ1336938

V. Pereyra

Publication date: 6 November 1994

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0167-7152(94)90055-8

zbMATH Keywords

bootstraprates of convergencekernel density estimationstationary time seriesstationary sequence of random variablesmean square consistencybandwidth choicecommon densitygrouped jackknife

Mathematics Subject Classification ID

Density estimation (62G07) Nonparametric statistical resampling methods (62G09)

Cites Work

• On the asymptotic properties of the jackknife histogram
• The use of subseries values for estimating the variance of a general statistic from a stationary sequence
• Some asymptotic theory for the bootstrap
• On the asymptotic accuracy of Efron's bootstrap
• On the sample variance of linear statistics derived from mixing sequences
• The asymptotic distribution theory of the empiric cdf for mixing stochastic processes
• Bootstrap methods: another look at the jackknife
• The jackknife and the bootstrap for general stationary observations
• Replicate Histograms
• A CENTRAL LIMIT THEOREM AND A STRONG MIXING CONDITION
• Approximation Theorems of Mathematical Statistics
• A note on proving that the (modified) bootstrap works
• Curve Estimates
• On Estimation of a Probability Density Function and Mode
• The bootstrap and Edgeworth expansion
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