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

Second-order quasi-likelihood for spatial point processes.

Chong Deng1, Yongtao Guan2, Rasmus P Waagepetersen3

  • 1Program in Applied Mathematics, Yale University, New Haven, Connecticut 06511, U.S.A.

Biometrics
|April 4, 2017
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

Improving RGB image recognition in the YOLO11n algorithm for accurate detection of tea plant diseases.

Journal of Zhejiang University. Science. B·2026
Same author

Effects of esculetin on growth performance, carcass traits, intestinal morphology, digestive enzyme, barrier function and cecal microbiota in broiler chickens.

Poultry science·2026
Same author

Species Dependent Toxicity Comparison Outcome.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2026
Same author

Eukaryotic elongation factor 2 kinase (eEF2K): Mechanisms and pharmacological significance in metabolic diseases.

International journal of biological macromolecules·2026
Same author

Transforming growth factor Beta/Smad3/GATA3 axis mediates the therapeutic effect of Ephedra sinica Stapf polysaccharide in allergic rhinitis.

Journal of leukocyte biology·2026
Same author

A Glycopeptide Mosaic Vaccine Elicits Robust Antitumor Immunity by Targeting Glycan Heterogeneity.

JACS Au·2026
Same journal

Fast penalized generalized estimating equations for large longitudinal functional datasets.

Biometrics·2026
Same journal

Causally-interpretable random-effects meta-analysis.

Biometrics·2026
Same journal

Statistical inference for mean function of partially observed functional time series.

Biometrics·2026
Same journal

Subgroup identification via Interaction Tree and Mixed Model for Repeated Measures with application to Alzheimer's disease.

Biometrics·2026
Same journal

Finite mixtures of linear quantile regressions with concomitant variables: a solution to endogeneity in longitudinal data modeling.

Biometrics·2026
Same journal

Discussion on "INTACT: a method for integration of longitudinal physical activity data from multiple sources" by Jingru Zhang, Erjia Cui, Hongzhe Li, and Haochang Shou.

Biometrics·2026
See all related articles

We developed a new statistical method for analyzing complex spatial data, improving efficiency in ecology. This approach enhances parameter estimation for spatial point processes, offering significant statistical gains.

Area of Science:

  • Ecology
  • Spatial Statistics
  • Computational Statistics

Background:

  • Analyzing large, complex ecological datasets with spatial point processes presents challenges in statistical and computational efficiency.
  • Inhomogeneities in data, common in fields like tropical rain forest ecology, necessitate advanced estimation methods.

Purpose of the Study:

  • To propose a novel, efficient method for parameter estimation in second-order intensity reweighted stationary spatial point processes.
  • To enhance both statistical and computational efficiency for analyzing spatial point process data.

Main Methods:

  • Developed a second-order quasi-likelihood procedure.
  • Derived and linearly combined first- and second-order estimating functions using optimal weight functions.
  • Exploited simplifications for stationary and nonstationary cases, focusing on lags between locations.
Keywords:
Estimating functionGodambe informationIntensity functionOptimalityPair correlation function

Related Experiment Videos

Main Results:

  • Achieved significant gains in statistical efficiency compared to existing methods through simulations.
  • Demonstrated considerable improvements in computational efficiency.
  • Successfully applied the procedure to a tropical rain forest dataset.

Conclusions:

  • The proposed second-order quasi-likelihood method offers a statistically and computationally efficient solution for spatial point process analysis.
  • This approach is particularly advantageous for large, complex, and inhomogeneous datasets, such as those found in ecological studies.
  • The method provides a valuable tool for researchers needing robust parameter estimation in spatial point process models.