Bộ sách luyện thi ETS 2023 LC&RC
199,000₫
299,000₫
Sách Bayesian Statistical Modeling with Stan, R, and Python (Sách keo gáy, bìa mềm)
Thể loại:Mathematics - Mathematical Statistics
Năm:2023
Ngôn ngữ:english
Trang:395
This book provides a highly practical introduction to Bayesian
statistical modeling with Stan, which has become the most popular
probabilistic programming language. The book is divided into four parts.
The first part reviews the theoretical background of modeling and
Bayesian inference and presents a modeling workflow that makes modeling
more engineering than art. The second part discusses the use of Stan,
CmdStanR, and CmdStanPy from the very beginning to basic regression
analyses. The third part then introduces a number of probability
distributions, nonlinear models, and hierarchical (multilevel) models,
which are essential to mastering statistical modeling. It also describes
a wide range of frequently used modeling techniques, such as censoring,
outliers, missing data, speed-up, and parameter constraints, and
discusses how to lead convergence of MCMC. Lastly, the fourth part
examines advanced topics for real-world data: longitudinal data
analysis, state space models, spatial data analysis, Gaussian processes,
Bayesian optimization, dimensionality reduction, model selection, and
information criteria, demonstrating that Stan can solve any one of these
problems in as little as 30 lines. Using numerous easy-to-understand
examples, the book explains key concepts, which continue to be useful
when using future versions of Stan and when using other statistical
modeling tools. The examples do not require domain knowledge and can be
generalized to many fields. The book presents full explanations of code
and math formulas, enabling readers to extend models for their own
problems. All the code and data are on GitHub.
