2nd ed. — Springer, 2025. — 496 p. — (Springer Texts in Statistics). — ISBN 107164131X.
This book,
Statistical Modeling and Computation, provides a unique introduction to
modern statistics from
both classical and Bayesian perspectives. It also offers an
integrated treatment of mathematical statistics and modern
statistical computation, emphasizing statistical modeling, computational techniques, and applications.
The 2nd. edition changes the programming language used in the text from MatLAB to
Julia. For all examples with computing components, the authors provide data sets and
their own Julia codes.
The new edition features numerous
full color graphics to illustrate the concepts discussed in the text, and adds three entirely
new chapters on a variety of popular topics, including:
Regularization and the Lasso regression.
Bayesian shrinkage methods.
Nonparametric statistical tests.
Splines and the Gaussian process regression.
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