Strong approximation of empirical process with independent but non- identically distributed random variables

DOI10.1007/BF02057589zbMath0627.60038OpenAlexW1963507724MaRDI QIDQ1092509

Zu Kang Zheng

Publication date: 1987

Published in: Acta Mathematicae Applicatae Sinica. English Series (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf02057589

zbMATH Keywords

empirical processasymptotic properties of the empirical processtwo- parameter Gaussian process

Mathematics Subject Classification ID

Random fields (60G60) Gaussian processes (60G15) Strong limit theorems (60F15)

Cites Work

• Approximation theorems for independent and weakly dependent random vectors
• An approximation of partial sums of independent RV'-s, and the sample DF. I
• An almost sure invariance principle for the empirical distribution function of mixing random variables
• Reproducing kernel Hilbert spaces and the law of the iterated logarithm for Gaussian processes
• An asymptotic representation of the sample distribution function
• Skorohod embedding of multivariate RV's, and the sample DF

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