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A Case Study Competition Among Methods for Analyzing Large Spatial Data
A Case Study Competition Among Methods for Analyzing Large Spatial Data
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A Case Study Competition Among Methods for Analyzing Large Spatial Data

Heaton, Matthew J. ; Datta, Abhirup ; Finley, Andrew O. ; Furrer, Reinhard ; Guinness, Joseph ; Guhaniyogi, Rajarshi ; Gerber, Florian ; Gramacy, Robert B. ; Hammerling, Dorit ; Katzfuss, Matthias ; Lindgren, Finn ; Nychka, Douglas W. ; Sun, Furong ; Zammit-Mangion, Andrew

Journal of agricultural, biological, and environmental statistics, 2019-09, Vol.24 (3), p.398-425 [Periódico revisado por pares]

New York: Springer Science + Business Media

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2
Characterization of Weighted Quantile Sum Regression for Highly Correlated Data in a Risk Analysis Setting
Characterization of Weighted Quantile Sum Regression for Highly Correlated Data in a Risk Analysis Setting
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Characterization of Weighted Quantile Sum Regression for Highly Correlated Data in a Risk Analysis Setting

Carrico, Caroline ; Gennings, Chris ; Wheeler, David C. ; Factor-Litvak, Pam

Journal of agricultural, biological, and environmental statistics, 2015-03, Vol.20 (1), p.100-120 [Periódico revisado por pares]

Boston: Springer Science+Business Media, LLC

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3
Selecting the Number of States in Hidden Markov Models: Pragmatic Solutions Illustrated Using Animal Movement
Selecting the Number of States in Hidden Markov Models: Pragmatic Solutions Illustrated Using Animal Movement
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Selecting the Number of States in Hidden Markov Models: Pragmatic Solutions Illustrated Using Animal Movement

Pohle, Jennifer ; Langrock, Roland ; van Beest, Floris M. ; Schmidt, Niels Martin

Journal of agricultural, biological, and environmental statistics, 2017-09, Vol.22 (3), p.270-293 [Periódico revisado por pares]

New York: Springer

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4
Vecchia Approximations of Gaussian-Process Predictions
Vecchia Approximations of Gaussian-Process Predictions
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Vecchia Approximations of Gaussian-Process Predictions

Katzfuss, Matthias ; Guinness, Joseph ; Gong, Wenlong ; Zilber, Daniel

Journal of agricultural, biological, and environmental statistics, 2020-09, Vol.25 (3), p.383-414 [Periódico revisado por pares]

New York: Springer Science + Business Media

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5
A Comparison of Bayesian Approximation Methods for Analyzing Large Spatial Skewed Data
A Comparison of Bayesian Approximation Methods for Analyzing Large Spatial Skewed Data
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A Comparison of Bayesian Approximation Methods for Analyzing Large Spatial Skewed Data

Roy, Paritosh Kumar ; Schmidt, Alexandra M.

Journal of agricultural, biological, and environmental statistics, 2024-07 [Periódico revisado por pares]

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6
Hierarchical Bayesian Integrated Modeling of Age- and Sex-Structured Wildlife Population Dynamics
Hierarchical Bayesian Integrated Modeling of Age- and Sex-Structured Wildlife Population Dynamics
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Hierarchical Bayesian Integrated Modeling of Age- and Sex-Structured Wildlife Population Dynamics

Mukhopadhyay, Sabyasachi ; Piepho, Hans-Peter ; Bhattacharya, Sourabh ; Dublin, Holly T. ; Ogutu, Joseph O.

Journal of agricultural, biological, and environmental statistics, 2024-07 [Periódico revisado por pares]

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7
Efficient Augmented Block Designs for Unreplicated Test Treatments Along with Replicated Controls
Efficient Augmented Block Designs for Unreplicated Test Treatments Along with Replicated Controls
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Efficient Augmented Block Designs for Unreplicated Test Treatments Along with Replicated Controls

Mukerjee, Rahul

Journal of agricultural, biological, and environmental statistics, 2024-06 [Periódico revisado por pares]

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8
Random Graphical Model of Microbiome Interactions in Related Environments
Random Graphical Model of Microbiome Interactions in Related Environments
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Random Graphical Model of Microbiome Interactions in Related Environments

Vinciotti, Veronica ; Wit, Ernst C. ; Richter, Francisco

Journal of agricultural, biological, and environmental statistics, 2024-06 [Periódico revisado por pares]

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9
A Modified Bayesian Optimization Approach for Determining a Training Set to Identify the Best Genotypes from a Candidate Population in Genomic Selection
A Modified Bayesian Optimization Approach for Determining a Training Set to Identify the Best Genotypes from a Candidate Population in Genomic Selection
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A Modified Bayesian Optimization Approach for Determining a Training Set to Identify the Best Genotypes from a Candidate Population in Genomic Selection

Tu, Hui-Ning ; Liao, Chen-Tuo

Journal of agricultural, biological, and environmental statistics, 2024-06 [Periódico revisado por pares]

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10
Borrowing Historical Information Across All Concentration Groups with an Application of Potency Estimation in Aquatic Toxicity Assessment
Borrowing Historical Information Across All Concentration Groups with an Application of Potency Estimation in Aquatic Toxicity Assessment
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Borrowing Historical Information Across All Concentration Groups with an Application of Potency Estimation in Aquatic Toxicity Assessment

Wang, Shixuan ; Zhang, Jing ; Zhang, Bin

Journal of agricultural, biological, and environmental statistics, 2024-06 [Periódico revisado por pares]

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