On almost sure convergence rates for the kernel estimator of a covariance operator under negative association

DOI10.22103/jmmr.2024.22733.1561MaRDI QIDQ6649142

Hadi Jabbari

Publication date: 5 December 2024

Published in: Journal of Mahani Mathematical Research Center (Search for Journal in Brave)

zbMATH Keywords

kernel estimationempirical processalmost sure convergence ratebivariate distribution function

Mathematics Subject Classification ID

Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05) Strong limit theorems (60F15)

Cites Work

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• Complete convergence of weighted sums under negative dependence
• On the strong convergence for weighted sums of random variables
• Exponential inequality for negatively associated random variables
• Strong convergence rates for the estimation of a covariance operator for associated samples
• A note on the universal consistency of the kernel distribution function estimator
• Normal fluctuations and the FKG inequalities
• Moment inequalities and weak convergence for negatively associated sequences
• A central limit theorem for random fields of negatively associated processes
• A comparison theorem on moment inequalities between negatively associated and independent random variables
• Negative association of random variables, with applications
• Estimation of a two-dimensional distribution function under association
• A note on the TJW product-limit estimator for truncated and censored data
• Asymptotic normality and strong consistency of LS estimators in the EV regression model with NA errors
• On almost sure convergence for weighted sums of pairwise negatively quadrant dependent random variables
• Local-Likelihood Transformation Kernel Density Estimation for Positive Random Variables

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