Innovations to Increase the Power of State-of-the Art Graph-Theoretic Two-Sample Statistical Tests

Abstract

One of the classic problems in statistics is to determine whether a group of observations can be characterized as statistically different from some other group. In the case of the well-known two-sample t-test, observations are univariate (1-dimensional) and underlying probability distributions are normal (or approximately normal). However, in real-world problems, the number of covariates may be very large and there may be little known about underlying distributions. Finding powerful tests for group differences in this general multivariate case presents challenges, and this difficult case has attracted recent research interest.

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Document Details

Document Type
Technical Report
Publication Date
May 21, 2018
Accession Number
AD1054423

Entities

People

  • Michael J. Wallace

Organizations

  • United States Naval Academy

Tags

Communities of Interest

  • Biomedical
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Cardiovascular Physiological Phenomena
  • Computer Science
  • Covariance
  • Data Science
  • Data Set
  • Data Sets
  • Databases
  • Digital Data
  • Information Science
  • Network Science
  • Normal Distribution
  • Permutations
  • Probability
  • Probability Distributions
  • Random Variables
  • Simulations
  • Statistical Algorithms
  • Statistical Analysis
  • Statistical Distributions
  • Statistical Tests
  • Statistics
  • Two Dimensional
  • United States Naval Academy

Fields of Study

  • Mathematics

Readers

  • Neural Network Machine Learning.
  • Regression Analysis.
  • Statistical inference.