Stationary Time Series, Quantile Functions, Nonparametric Inference and Rank Transform Spectrum.

Abstract

In this dissertation, weak convergence results for dependent sequences are used to derive the asymptotic distribution of linear rank statistics for the two sample problem. It is shown that the asymptotic variance of linear rank statistics when computed from two independent time series depends on the spectrum of the rank transform time series. The behavior of the rank transform spectrum in terms of its relations to the original spectrum is also empirically examined. Keywords: Wilcoxon tests. (Author)

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1985
Accession Number
ADA161749

Entities

People

  • Avrahan Harpaz

Organizations

  • Texas A&M University

Tags

Communities of Interest

  • Air Platforms
  • C4I
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Asymptotic Normality
  • Data Analysis
  • Data Mining
  • Data Science
  • Data Sets
  • Distribution Functions
  • Gaussian Processes
  • Information Science
  • Military Research
  • Normal Distribution
  • Radio Frequency
  • Random Variables
  • Statistical Algorithms
  • Statistical Analysis
  • Stochastic Processes
  • Universities
  • Weak Convergence

Fields of Study

  • Mathematics

Readers

  • Statistical inference.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms