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 separability in spatial-temporal marked point processes.

Frederic Paik Schoenberg1

  • 1Department of Statistics, 8142 Math-Science Building, University of California, Los Angeles 90095-1554, USA. frederic@stat.ucla.edu

Biometrics
|June 8, 2004
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

A non-parametric Hawkes model of the spread of Ebola in west Africa.

Journal of applied statistics·2022
Same author

Real-time predictions of the 2018-2019 Ebola virus disease outbreak in the Democratic Republic of the Congo using Hawkes point process models.

Epidemics·2019
Same author

Living with avian FLU--Persistence of the H5N1 highly pathogenic avian influenza virus in Egypt.

Veterinary microbiology·2016
Same author

Neurodevelopmental delay in children exposed in utero to hyperemesis gravidarum.

European journal of obstetrics, gynecology, and reproductive biology·2015
Same author

Psychiatric factors do not affect recurrence risk of hyperemesis gravidarum.

The journal of obstetrics and gynaecology research·2014
Same author

Antihistamines and other prognostic factors for adverse outcome in hyperemesis gravidarum.

European journal of obstetrics, gynecology, and reproductive biology·2013

This study introduces nonparametric tests to analyze spatial-temporal marked point processes. Findings reveal that fire clustering, particularly of similar sizes, invalidates the separability hypothesis in wildfire data.

Area of Science:

  • Spatial statistics
  • Point process analysis
  • Environmental science

Background:

  • Investigating spatial-temporal marked point processes is crucial for understanding complex phenomena.
  • The assumption of separability simplifies analysis but may not reflect reality.

Purpose of the Study:

  • To describe and compare nonparametric tests for spatial-temporal marked point process separability.
  • To identify powerful statistical methods for detecting departures from separability.

Main Methods:

  • Comparison of Cramer-von Mises-type tests for gradual departures.
  • Utilizing residual tests based on random rescaling for clustering/inhibition detection.
  • Application to Los Angeles County wildfire data.

Related Experiment Videos

Main Results:

  • Cramer-von Mises tests effectively detect gradual deviations from separability.
  • Residual tests are powerful in identifying nonseparable clustering or inhibition.
  • Wildfire data analysis invalidated the separability hypothesis.

Conclusions:

  • Nonparametric tests provide robust methods for assessing spatial-temporal marked point process separability.
  • Wildfire occurrences exhibit nonseparable clustering of similar sizes over time.
  • The findings have implications for understanding and modeling spatial-temporal environmental events.