Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Testing local dependence of spatial structures on images

Chadoeuf1, Brix, Pierret

  • 1Biometrie, INRA, Domaine St Paul, 84914 Avignon Cedex 9, France; Department of Mathematics and Statistics, Lancaster University, U.K. ; CSIRO Land and Water, Butler Laboratory, GPO Box 1666, Canberra ACT 2601, Australia.

Journal of Microscopy
|September 30, 2000
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Plasma fibronectin in French centenarians.

Archives of gerontology and geriatrics·2000
Same author

Determination of the molecular weight of fulvic acids by UV/VIS spectroscopy

Chemosphere·2000
Same author

The complete homogeneous master equation for a heteronuclear two-spin system in the basis of cartesian product operators

Journal of magnetic resonance (San Diego, Calif. : 1997)·1998
Same author

A method for simulation of NOESY, ROESY, and off-resonance ROESY spectra

Journal of magnetic resonance (San Diego, Calif. : 1997)·1998
Same author

NMR Relaxation Mechanisms for Backbone Carbonyl Carbons in a 13 C, 15 N-Labeled Protein

Journal of magnetic resonance (San Diego, Calif. : 1997)·1997
Same author

Phase-Sensitive Two-Dimensional Heteronuclear Zero- and Double-Quantum-Coherence Spectroscopy

Journal of magnetic resonance. Series B·1996

This study introduces local statistical tests to differentiate true spatial dependence from common underlying factors. These methods create interaction maps and assess spatial patterns in various microscopic images.

Area of Science:

  • Spatial Statistics
  • Geostatistics
  • Image Analysis

Background:

  • Spatial processes can exhibit apparent associations due to shared unobserved variables, complicating the identification of genuine interactions.
  • Distinguishing true spatial dependence from confounding factors is crucial for accurate analysis of spatial data.

Purpose of the Study:

  • To develop and validate local statistical tests for detecting real dependence between spatial processes.
  • To create a global test for real dependence and generate maps illustrating local spatial interactions.
  • To extend these methods for testing non-stationarity in point patterns and interactions with censoring processes.

Main Methods:

  • Integration of classical interaction tests (e.g., Berman's random rotations) into local analysis frameworks.

Related Experiment Videos

  • Local performance of statistical tests and comparison of p-value distributions against null hypotheses.
  • Application of distance statistics (popularized by Diggle) for testing point pattern non-stationarity.

    • Main Results:

    • Demonstrated the efficacy of local tests in identifying genuine spatial dependencies.
    • Developed a methodology for mapping local spatial interactions, providing detailed insights into spatial structures.
    • Successfully adapted methods to analyze interactions between random fields and censoring processes.

    Conclusions:

    • The proposed local testing approach effectively distinguishes true spatial dependence from indirect associations.
    • The developed methods offer a robust framework for analyzing spatial structures in diverse microscopic images.
    • These techniques are broadly applicable, particularly in agricultural science and other fields requiring spatial analysis.