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Jay M. Ver Hoef

National Oceanic and Atmospheric Administration
National Marine Fisheries Service
Alaska Department of Fish and Game

151

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Bayesian spatio-temporal models for stream networks.

2022 Comput. Stat. Data Anal.
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Author response for "Species density models from opportunistic citizen science data"

2021
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On Deconfounding Spatial Confounding in Linear Models

2021 The American Statistician
- Dale L. Zimmerman
- Jay M. Ver Hoef
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A linear mixed model formulation for spatio-temporal random processes with computational advances for the product, sum, and product–sum covariance functions

2021 spatial statistics
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Application of a Bayesian hierarchical model to estimate trends in Atlantic harbor seal (Phoca vitulina vitulina) abundance in Maine, U.S.A., 1993–2018

2021 Marine Mammal Science
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Species density models from opportunistic citizen science data

2021 Methods in Ecology and Evolution
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Report of the NAMMCO-ICES Workshop on Seal Modelling (WKSEALS 2020)

2021 Nammco Scientific Publications
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Bayesian spatio-temporal models for stream networks.

2021 arXiv: Methodology
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Robustness of close‐kin mark–recapture estimators to dispersal limitation and spatially varying sampling probabilities

2020 Ecology and Evolution
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Comparing spatial regression to random forests for large environmental data sets.

2020 PLOS ONE
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