Multi-Sample Functional Statistical Data Analysis

Abstract

This paper discusses a functional approach to the problem of comparison of multi-samples (two samples or c samples, where c > or = 2). The data consists of c random samples whose probability distributions are to be tested for equality. A diversity of statistics to test equality of c samples are presented in a unified framework with the aim of helping the researcher choose the optimal procedures which provide greatest insight about how the samples differ in their distributions. Concepts discussed are: sample distribution functions; ranks; mid-distribution function; two- sample t test and nonparametric Wilcoxon test; multi-sample analysis of variance and Kruskal Wallis test; Anderson Darling and Cramer von Mises tests; components and linear rank statistics; comparison distribution and comparison density functions, especially for discrete distributions; components with orthogonal polynomial score functions; chi-square tests and their components.

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Document Details

Document Type
Technical Report
Publication Date
May 01, 1989
Accession Number
ADA210992

Entities

People

  • Emanuel Parzen

Organizations

  • Texas A&M University

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Analysis Of Variance
  • Data Analysis
  • Data Mining
  • Data Science
  • Discrete Distribution
  • Distribution Functions
  • Information Science
  • Military Research
  • Polynomials
  • Probability
  • Probability Distributions
  • Random Variables
  • Statistical Analysis
  • Statistical Data
  • Statistical Samples
  • Statistics

Fields of Study

  • Mathematics

Readers

  • Regression Analysis.
  • Statistical inference.