References

R packages

This book was produced using all the following R packages

A large number of files (2806 in total) have been discovered.
It may take renv a long time to crawl these files for dependencies.
Consider using .renvignore to ignore irrelevant files.
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Set `options(renv.config.dependencies.limit = Inf)` to disable this warning.
Package Version Citation
abind 1.4.5 Plate and Heiberger (2016)
asreml 4.2.0.302 The VSNi Team (2023)
base 4.4.1 R Core Team (2024)
brms 2.21.0 Bürkner (2017); Bürkner (2018); Bürkner (2021)
knitr 1.48 Xie (2014); Xie (2015); Xie (2024)
lme4 1.1.35.5 Bates et al. (2015)
MCMCglmm 2.36 Hadfield (2010)
nadiv 2.18.0 Wolak (2012)
rmarkdown 2.28 Xie et al. (2018); Xie et al. (2020); Allaire et al. (2024)
rptR 0.9.22 Stoffel et al. (2017)
tidyverse 2.0.0 Wickham et al. (2019)
visreg 2.7.0 Breheny and Burchett (2017)

Bibliography

Allaire, J., Y. Xie, C. Dervieux, J. McPherson, J. Luraschi, K. Ushey, A. Atkins, H. Wickham, J. Cheng, W. Chang, and R. Iannone. 2024. rmarkdown: Dynamic documents for r.
Bates, D., M. Mächler, B. Bolker, and S. Walker. 2015. Fitting linear mixed-effects models using lme4. Journal of Statistical Software 67:1–48.
Breheny, P., and W. Burchett. 2017. Visualization of regression models using visreg. The R Journal 9:56–71.
Bürkner, P.-C. 2017. brms: An R package for Bayesian multilevel models using Stan. Journal of Statistical Software 80:1–28.
Bürkner, P.-C. 2018. Advanced Bayesian multilevel modeling with the R package brms. The R Journal 10:395–411.
Bürkner, P.-C. 2021. Bayesian item response modeling in R with brms and Stan. Journal of Statistical Software 100:1–54.
Hadfield, J. D. 2010. MCMC methods for multi-response generalized linear mixed models: The MCMCglmm R package. Journal of Statistical Software 33:1–22.
Martin, J., M. Wolak, S. Johnston, and M. Morrissey. 2024. Pedtricks: Visualize, summarize and simulate data from pedigrees.
Plate, T., and R. Heiberger. 2016. abind: Combine multidimensional arrays.
R Core Team. 2024. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria.
Stoffel, M. A., S. Nakagawa, and H. Schielzeth. 2017. rptR: Repeatability estimation and variance decomposition by generalized linear mixed-effects models. Methods in Ecology and Evolution 8:1639???1644.
The VSNi Team. 2023. asreml: Fits linear mixed models using REML.
Wickham, H., M. Averick, J. Bryan, W. Chang, L. D. McGowan, R. François, G. Grolemund, A. Hayes, L. Henry, J. Hester, M. Kuhn, T. L. Pedersen, E. Miller, S. M. Bache, K. Müller, J. Ooms, D. Robinson, D. P. Seidel, V. Spinu, K. Takahashi, D. Vaughan, C. Wilke, K. Woo, and H. Yutani. 2019. Welcome to the tidyverse. Journal of Open Source Software 4:1686.
Wilson, A. J., D. Réale, M. N. Clements, M. M. Morrissey, E. Postma, C. A. Walling, L. E. B. Kruuk, and D. H. Nussey. 2010. An ecologist’s guide to the animal model. Journal of Animal Ecology 79:13–26.
Wolak, M. E. 2012. nadiv: An R package to create relatedness matrices for estimating non-additive genetic variances in animal models. Methods in Ecology and Evolution 3:792–796.
Xie, Y. 2014. knitr: A comprehensive tool for reproducible research in R. in V. Stodden, F. Leisch, and R. D. Peng, editors. Implementing reproducible computational research. Chapman; Hall/CRC.
Xie, Y. 2015. Dynamic documents with R and knitr. 2nd edition. Chapman; Hall/CRC, Boca Raton, Florida.
Xie, Y. 2024. knitr: A general-purpose package for dynamic report generation in r.
Xie, Y., J. J. Allaire, and G. Grolemund. 2018. R markdown: The definitive guide. Chapman; Hall/CRC, Boca Raton, Florida.
Xie, Y., C. Dervieux, and E. Riederer. 2020. R markdown cookbook. Chapman; Hall/CRC, Boca Raton, Florida.