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Statistical Rethinking - A Bayesian Course with Examples in R and Stan (Hardcover)
Loot Price: R2,501
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Statistical Rethinking - A Bayesian Course with Examples in R and Stan (Hardcover)
Series: Chapman & Hall/CRC Texts in Statistical Science
Expected to ship within 9 - 15 working days
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Statistical Rethinking: A Bayesian Course with Examples in R and
Stan builds readers' knowledge of and confidence in statistical
modeling. Reflecting the need for even minor programming in today's
model-based statistics, the book pushes readers to perform
step-by-step calculations that are usually automated. This unique
computational approach ensures that readers understand enough of
the details to make reasonable choices and interpretations in their
own modeling work. The text presents generalized linear multilevel
models from a Bayesian perspective, relying on a simple logical
interpretation of Bayesian probability and maximum entropy. It
covers from the basics of regression to multilevel models. The
author also discusses measurement error, missing data, and Gaussian
process models for spatial and network autocorrelation. By using
complete R code examples throughout, this book provides a practical
foundation for performing statistical inference. Designed for both
PhD students and seasoned professionals in the natural and social
sciences, it prepares them for more advanced or specialized
statistical modeling. Web Resource The book is accompanied by an R
package (rethinking) that is available on the author's website and
GitHub. The two core functions (map and map2stan) of this package
allow a variety of statistical models to be constructed from
standard model formulas.
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