Bernstein-type large deviations inequalities for partial sums of strong mixing processes

DOI10.1080/02331888308802389zbMath0810.60027OpenAlexW1971573271MaRDI QIDQ4324712

Denis Bosq

Publication date: 28 February 1995

Published in: Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02331888308802389

zbMATH Keywords

strong law of large numberslarge deviationsstrong mixingnonparametric regression

Mathematics Subject Classification ID

Density estimation (62G07) Strong limit theorems (60F15) Large deviations (60F10)

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Cites Work

• Unnamed Item
• Unnamed Item
• Large Sample Properties of Generalized Method of Moments Estimators
• On Large-Sample Estimation and Testing in Parametric Models
• A Method of Generating Best Asymptotically Normal Estimates with Application to the Estimation of Bacterial Densities
• Approximation Theorems of Mathematical Statistics
• The X^2 Goodness of Fit Statistic for Models with Parameters Estimated from Microdata
• A chi-squabe statistic for goodies-of-fit tests within the exponential family
• Chi-Square Test for Continuous Distributions with Shift and Scale Parameters
• On a Modification of the Standard Statistics of Pearson
• On Simplified Estimators of Unknown Parameters with Good Asymptotic Properties
• The Use of Maximum Likelihood Estimates in $\chi^2$ Tests for Goodness of Fit

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