Abstract
The Roadmap is a section that will start each chapter by providing a commented table of contents. It also usually contains indications on the purpose of the chapter.
The bare essentials, in other words.
—Ian Rankin, Tooth & Nail.—
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Notes
- 1.
If you decide to skip this chapter, be sure to at least print the handy R Reference Card available at http://cran.r-project.org/doc/contrib/Short-refcard.pdf that summarizes, in four pages, the major commands of R.
- 2.
Once again, R is a freely distributed and open-source language.
- 3.
The main CRAN Website is http://cran.r-project.org/.
- 4.
Packages that have been validated and tested by the R core team are listed at http://cran.r-project.org/src/contrib/PACKAGES.html.
- 5.
The variable e is not predefined in R as exp(1).
- 6.
Positive and negative indices cannot be used simultaneously.
- 7.
Lists can contain lists as elements.
References
Carlin, B. and Louis, T. (1996). Bayes and Empirical Bayes Methods for Data Analysis. Chapman and Hall, New York.
Casella, G. and Berger, R. (2001). Statistical Inference. Wadsworth, Belmont, CA.
Chen, M., Shao, Q., and Ibrahim, J. (2000). Monte Carlo Methods in Bayesian Computation. Springer-Verlag, New York.
Congdon, P. (2001). Bayesian Statistical Modelling. John Wiley, New York.
Congdon, P. (2003). Applied Bayesian Modelling. John Wiley, New York.
Crawley, M. (2007). The R Book. John Wiley, New York.
Dalgaard, P. (2002). Introductory Statistics with R. Springer-Verlag, New York.
Gelman, A., Carlin, J., Stern, H., and Rubin, D. (2013). Bayesian Data Analysis. Chapman and Hall, New York, second edition.
Gelman, A., Carlin, J., Stern, H., Dunson, D., Vehtari, A. and Rubin, D. (2013). Bayesian Data Analysis. Chapman and Hall, New York, New York, third edition.
Gill, J. (2002). Bayesian Methods: A Social and Behavioral Sciences Approach. CRC Press, Boca Raton, FL.
Hoff, P. (2009). A first course in Bayesian statistical methods. Springer-Verlag, New York.
Holmes, C., Denison, D., Mallick, B., and Smith, A. (2002). Bayesian Methods for Nonlinear Classification and Regression. John Wiley, New York.
Lunn, D., Jackson, C., Best, N., Thomas, A., and Spiegelhalter, D. (2012). The BUGS Book: A Practical Introduction to Bayesian Analysis. Chapman and Hall/CRC, London, UK.
Murrell, P. (2005). R Graphics. Chapman and Hall, New York.
Nolan, D. and Speed, T. (2000). Stat Labs: Mathematical Statistics through Applications. Springer-Verlag, New York.
Pole, A., West, M., and Harrison, J. (1994). Applied Bayesian Forecasting and Time Series Analysis. Chapman and Hall, New York.
Robert, C. (2007). The Bayesian Choice. Springer-Verlag, New York, paperback edition.
Robert, C. and Casella, G. (2004). Monte Carlo Statistical Methods. Springer-Verlag, New York, second edition.
Robert, C. and Casella, G. (2009). Introducing Monte Carlo Methods with R. Use R! Springer-Verlag, New York.
Spector, P. (2009). Data Manipulation with R. Springer-Verlag, New York.
Tufte, E. (2001). The Visual Display of Quantitative Information. Graphics Press, second edition.
Venables, W. and Ripley, B. (2002). Modern Applied Statistics with S. Springer-Verlag, New York, fourth edition.
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Marin, JM., Robert, C.P. (2014). User’s Manual. In: Bayesian Essentials with R. Springer Texts in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8687-9_1
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