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Jay M Ver Hoef

Showing results (11-20 of 36) with videos related to

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Ecology and Evolution|July 2, 2020
Robustness of close-kin mark-recapture estimators to dispersal limitation and spatially varying sampling probabilitiesPaul B Conn, Mark V Bravington, Shane Baylis, et al.
Biometrics|December 1, 2007
A general framework for the analysis of animal resource selection from telemetry dataDevin S Johnson, Dana L Thomas, Jay M Ver Hoef, et al.
Methods in Ecology and Evolution|November 7, 2022
A comparison of design-based and model-based approaches for finite population spatial sampling and inferenceMichael Dumelle, Matt Higham, Jay M Ver Hoef, et al.
Risk Analysis : an Official Publication of the Society for Risk Analysis|March 24, 2018
A Bayesian Analysis of Abundance, Trend, and Population Viability for Harbor Seals in Iliamna Lake, AlaskaPeter L Boveng, Jay M Ver Hoef, David E Withrow, et al.
Plos One|July 2, 2015
Spatially Estimating Disturbance of Harbor Seals (Phoca vitulina)John K Jansen, Gavin M Brady, Jay M Ver Hoef, et al.
Journal of Wildlife Diseases|October 7, 2004
Prevalence of Soboliphyme baturini in marten (Martes americana) populations from three regions of Alaska, 1990-1998Randall L Zarnke, Jackson S Whitman, Rodney W Flynn, et al.
Plos One|November 1, 2023
Indexing and partitioning the spatial linear model for large data setsJay M Ver Hoef, Michael Dumelle, Matt Higham, et al.
Journal of Open Source Software|August 28, 2024
SSN2: The next generation of spatial stream network modeling in RMichael Dumelle, Erin E Peterson, Jay M Ver Hoef, et al.
Ecological Applications : a Publication of the Ecological Society of America|May 23, 2012
A Bayesian hierarchical model of Antarctic fur seal foraging and pup growth related to sea ice and prey abundanceLisa M Hiruki-Raring, Jay M Ver Hoef, Peter L Boveng, et al.
Ecological Applications : a Publication of the Ecological Society of America|May 12, 2009
Accounting for uncertainty in ecological analysis: the strengths and limitations of hierarchical statistical modelingNoel Cressie, Catherine A Calder, James S Clark, et al.
Pageof 4

Showing results (11-20 of 36) with videos related to

Sort By:
Pageof 4
Ecology and Evolution|July 2, 2020
Robustness of close-kin mark-recapture estimators to dispersal limitation and spatially varying sampling probabilitiesPaul B Conn, Mark V Bravington, Shane Baylis, et al.
Biometrics|December 1, 2007
A general framework for the analysis of animal resource selection from telemetry dataDevin S Johnson, Dana L Thomas, Jay M Ver Hoef, et al.
Methods in Ecology and Evolution|November 7, 2022
A comparison of design-based and model-based approaches for finite population spatial sampling and inferenceMichael Dumelle, Matt Higham, Jay M Ver Hoef, et al.
Risk Analysis : an Official Publication of the Society for Risk Analysis|March 24, 2018
A Bayesian Analysis of Abundance, Trend, and Population Viability for Harbor Seals in Iliamna Lake, AlaskaPeter L Boveng, Jay M Ver Hoef, David E Withrow, et al.
Plos One|July 2, 2015
Spatially Estimating Disturbance of Harbor Seals (Phoca vitulina)John K Jansen, Gavin M Brady, Jay M Ver Hoef, et al.
Journal of Wildlife Diseases|October 7, 2004
Prevalence of Soboliphyme baturini in marten (Martes americana) populations from three regions of Alaska, 1990-1998Randall L Zarnke, Jackson S Whitman, Rodney W Flynn, et al.
Plos One|November 1, 2023
Indexing and partitioning the spatial linear model for large data setsJay M Ver Hoef, Michael Dumelle, Matt Higham, et al.
Journal of Open Source Software|August 28, 2024
SSN2: The next generation of spatial stream network modeling in RMichael Dumelle, Erin E Peterson, Jay M Ver Hoef, et al.
Ecological Applications : a Publication of the Ecological Society of America|May 23, 2012
A Bayesian hierarchical model of Antarctic fur seal foraging and pup growth related to sea ice and prey abundanceLisa M Hiruki-Raring, Jay M Ver Hoef, Peter L Boveng, et al.
Ecological Applications : a Publication of the Ecological Society of America|May 12, 2009
Accounting for uncertainty in ecological analysis: the strengths and limitations of hierarchical statistical modelingNoel Cressie, Catherine A Calder, James S Clark, et al.
Pageof 4