LIMIT LAWS FOR EXTREME ORDER STATISTICS FROM STRONG-MIXING PROCESSES.

Abstract

The paper characterizes the possible limit laws for a sequence of normalized extreme order statistics (maximum, second maximum, etc.) from a stationary strong-mixing sequence of random variables. It extends the work of Loynes who considered only the maximum process. The maximum process leads to limit laws that are the same three types that occur when the underlying process is a sequence of independent random variables. The results presented here show that the possible limit laws for the k-th maximum process (k>1) from a strong-mixing sequence form a larger class than can occur in the independent case. (Author)

Document Details

Document Type
Technical Report
Publication Date
Apr 01, 1970
Accession Number
AD0710228

Entities

People

  • Roy E. Welsch

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Data Science
  • Information Science
  • Mathematics
  • Order Statistics
  • Probability
  • Random Variables
  • Sequences
  • Statistical Analysis
  • Statistics

Fields of Study

  • Mathematics

Readers

  • Mathematical Modeling and Probability Theory.