Testing for a Signal with Unknown Location and Scale in a Stationary Gaussian Random Field

Abstract

We suppose that our observations can be decomposed into a fixed signal plus random noise, where the noise is modelled as a particular stationary Gaussian random field in N-dimensional Euclidean space. The signal has the form of a known function centered at an unknown location and multiplied by an unknown amplitude, and we are primarily interested in a test to detect such a signal. There are many examples where the signal scale or width is assumed known, and the test is based on maximising a Gaussian random field over all locations in a subset of N-dimensional Euclidean space. The novel feature of this work is that the width of the signal is also unknown and the test is based on mzximising a Gaussian width. Two convergent approaches are used to approximate the null distribution: one based on the method of Knowles and Siegmund (1989), which uses a version of Weyl's (1939) tube (1993b), which uses the Hadwiger characteristic of excursion sets as introduced by Adler (1981). Finally we compared the power of our method with one based on a fixed but perhaps incorrect signal width.

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Document Details

Document Type
Technical Report
Publication Date
Jan 07, 1994
Accession Number
ADA275320

Entities

People

  • David O. Siegmund
  • Keith J. Worsley

Organizations

  • Stanford University

Tags

Communities of Interest

  • Biomedical
  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Covariance
  • Curvature
  • Data Science
  • Data Sets
  • Differential Geometry
  • Distribution Functions
  • Geometric Forms
  • Geometry
  • Information Science
  • Normal Distribution
  • Probability
  • Random Variables
  • Statistical Analysis
  • Statistics
  • Three Dimensional
  • United States
  • White Noise

Fields of Study

  • Engineering

Readers

  • Calculus or Mathematical Analysis
  • Statistical inference.

Technology Areas

  • Space