Skip to content
DraconiticResearch
Search Sources API
197,787 studies31 sourcesUpdated 59 min ago
Peer-reviewedCC BYJournal of the American Statistical Association

Bayesian Spatiotemporal Wombling

  • Aritra Halder1
  • Didong Li2
  • Sudipto Banerjee3
  1. 1Department of Biostatistics & Epidemiology, Drexel University, Philadelphia, PA
  2. 2Department of Biostatistics, University of North Carolina, Chapel Hill, NC
  3. 3Department of Biostatistics, University of California, Los Angeles, CA
Read full textPDFCite

Related

  1. Bayesian spatiotemporal conditional autoregressive model for local temporal variations
    Takahiro Onizuka, Shintaro Hashimoto
    arXivPreprintarXiv licenceFull textStatisticsarXiv
  2. Spatiotemporal Dynamics of Conway's Game of Life in the Entropy--Complexity Plane
    Lucas Malacarne Astore, Alejandro C. Frery, Petrônio Cândido de Lima e Silva +1
    arXivPreprintCC BY 4.0Full textGeneral mathematicsStatistical & nonlinear physicsarXiv
  3. From the SIR/SEIR/SVEIR Model to a Chemotactic System: Analysis of Spatiotemporal Mechanisms of Infection Spread within the Einstein Paradigm
    Yizhou Wang, Evgenia Echkina
    arXivPreprintarXiv licenceFull textEvolutionary biologyAnalysis & PDEsarXiv
  4. Spatiotemporal Response Decay for Near-Optimal Distributed LQR via System Level Synthesis
    Chenchen Zhou, José Matias
    arXivPreprintarXiv licenceFull textOptimisation & controlarXiv
  5. Fast covariance-free spatiotemporal modeling via coarse-to-fine learning
    Daisuke Murakami
    arXivPreprintarXiv licenceFull textStatisticsarXiv

Cite

BibTeXRIS
BibTeX
@article{halder2026bayesian,
  title = {{Bayesian Spatiotemporal Wombling}},
  author = {Aritra Halder and Didong Li and Sudipto Banerjee},
  journal = {Journal of the American Statistical Association},
  year = {2026},
  month = sep,
  url = {https://europepmc.org/article/PMC/PMC13664449},
  note = {CC BY},
}
RIS
TY  - JOUR
TI  - Bayesian Spatiotemporal Wombling
AU  - Aritra Halder
AU  - Didong Li
AU  - Sudipto Banerjee
PY  - 2026
DA  - 2026/09/08
JO  - Journal of the American Statistical Association
UR  - https://europepmc.org/article/PMC/PMC13664449
SN  - 0162-1459
SN  - 1537-274X
ER  -