Model selection with missing covariates for policy considerations in fox enclosures-Reference-Cited by-同舟云学术

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Model selection with missing covariates for policy considerations in fox enclosures

Published:2016-11-24 Issue:15 Volume:44 Page:2645-2658
ISSN:0266-4763
Container-title:Journal of Applied Statistics
language:en
Short-container-title:Journal of Applied Statistics

Author:

Hoegh Andrew¹,Crandell Ian²,Klopfer Scott³,Fies Mike⁴

Affiliation:

1. Department of Mathematical Sciences, Montana State University, Bozeman, MT, USA

2. Department of Statistics, Virginia Tech, Blacksburg, VA, USA

3. Conservation Management Institute, Virginia Tech, Blacksburg, VA, USA

4. Virginia Department of Game & Inland Fisheries, Verona, VA, USA

Publisher

Informa UK Limited

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Link

https://www.tandfonline.com/doi/pdf/10.1080/02664763.2016.1259401

Reference21 articles.

1. Bayesian Analysis of Binary and Polychotomous Response Data

2. Using data augmentation via the Gibbs Sampler to incorporate missing covariate structure in linear models for ecological assessments

3. M. Carzolio, On a selection of advanced Markov chain Monte Carlo algorithms for everyday use: Weighted particle tempering, practical reversible jump, and extensions, Ph.D. thesis, Virginia Tech, 2016.

4. Marginal Likelihood from the Gibbs Output

5. Marginal Likelihood From the Metropolis–Hastings Output

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1. Prior elicitation for Gaussian spatial process: An application to TMS brain mapping;Statistics in Medicine;2023-07-06

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