The Annals of Statistics

Weak Convergence of Empirical Distribution Functions of Random Variables Subject to Perturbations and Scale Factors

J. S. Rao and J. Sethuraman

Full-text: Open access

Abstract

The weak convergence of empirical distribution functions subject to random perturbations and scale factors to a Gaussian process is established. This result is used to study the efficiencies of tests based on spacings in goodness-of-fit problems.

Article information

Source
Ann. Statist., Volume 3, Number 2 (1975), 299-313.

Dates
First available in Project Euclid: 12 April 2007

Permanent link to this document
https://projecteuclid.org/euclid.aos/1176343058

Digital Object Identifier
doi:10.1214/aos/1176343058

Mathematical Reviews number (MathSciNet)
MR405671

Zentralblatt MATH identifier
0306.62007

JSTOR
links.jstor.org

Subjects
Primary: 62E20: Asymptotic distribution theory
Secondary: 62G20: Asymptotic properties 62G10: Hypothesis testing 60F05: Central limit and other weak theorems

Keywords
Weak convergence perturbations and scale factors empirical distribution functions spacings efficiencies of tests goodness-of-fit tests

Citation

Rao, J. S.; Sethuraman, J. Weak Convergence of Empirical Distribution Functions of Random Variables Subject to Perturbations and Scale Factors. Ann. Statist. 3 (1975), no. 2, 299--313. doi:10.1214/aos/1176343058. https://projecteuclid.org/euclid.aos/1176343058


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