Joint count transformation models with covariate‐dependent correlations

Modeling spatially dependent count time series data using COM-poisson INGARCH Models
Stephanie Colwell, Prabhakar Chalise, Byron Gajewski +2
PLOS One6 Oct 2026Peer-reviewedCC BY 4.0Full textAtmospheric science & meteorology StatisticsPLOS
Transformation product bottleneck: Photo-recalcitrance of rotenolone limits the aquatic degradation of rotenone in a temperature-dependent manner
Brian P. DiMento, Aidan Efird, Stefani Martinez +6
ChemRxiv11 Oct 2026PreprintCC BYFull textEnvironmental science & pollutionChemRxiv
Hidden periodicity in LiDAR point-count rasters
Alejandro Urias
EarthArXiv26 Sep 2026PreprintCC BY 4.0Full textGeophysics & seismologyEarthArXiv
The GRACE satellite mission and transformation of global groundwater science
Mohammad Shamsudduha, Richard G Taylor, Arifin +1
Environmental Research Letters22 Oct 2026Peer-reviewedCC BY 4.0Full textOceanography & cryosphereCrossref
Mechanical controls on the rate of phase transformations in deforming rocks: a numerical study applied to quartz-coesite transformation
Benedek Koszta, Kristóf Porkoláb, Philippe Yamato +1
EGUsphere5 Nov 2026PreprintCC BY 4.0General earth scienceEGUsphere

Cite

BibTeX

@article{graz2026joint,
  title = {{Joint count transformation models with covariate‐dependent correlations}},
  author = {Lukas Graz and Luisa Barbanti and Roland Brandl and Torsten Hothorn},
  journal = {Ecology.},
  year = {2026},
  month = oct,
  url = {https://europepmc.org/article/PMC/PMC13656892},
  note = {CC BY},
}

RIS

TY  - JOUR
TI  - Joint count transformation models with covariate‐dependent correlations
AU  - Lukas Graz
AU  - Luisa Barbanti
AU  - Roland Brandl
AU  - Torsten Hothorn
PY  - 2026
DA  - 2026/10/01
JO  - Ecology.
UR  - https://europepmc.org/article/PMC/PMC13656892
SN  - 0012-9658
ER  -

Related

Cite