Cumulative Processes: Linear Combinations of Order Statistics and Percentiles.

Abstract

Percentiles and linear combinations of order statistics are statistics which are sometimes preferred to averages because they can be less sensitive to the presence of a few wild observations. It is well known that for large samples, both percentiles and linear combinations of order statistics resemble averages in that the appropriately normalized statistic is approximately normally distributed, with parameters which depend on the underlying distributions. This paper shows that percentiles and linear combinations of order statistics resemble averages in a stronger sense. It is well known that if a sequence of averages is plotted against the number of observations contributing to the average, and the resulting plot is rescaled appropriately, then for long sequences the picture will act like a realization of a Brownian motion path. This paper establishes that this is still true if the averages are replaced by percentiles or by linear combinations of order statistics. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1980
Accession Number
ADA086372

Entities

People

  • Sue Leurgans

Organizations

  • University of Wisconsin–Madison

Tags

DTIC Thesaurus Topics

  • Asymptotic Normality
  • Brownian Motion
  • Data Science
  • Distribution Functions
  • Gaussian Processes
  • Information Science
  • Mathematics
  • Monotone Functions
  • Normal Distribution
  • Order Statistics
  • Probability
  • Random Variables
  • Sequences
  • Statistical Functions
  • Statistics
  • United States
  • Weak Convergence

Fields of Study

  • Mathematics

Readers

  • Approximation Theory.
  • Mathematical Modeling and Probability Theory.
  • Regression Analysis.