|
Books > Science & Mathematics > Mathematics > Probability & statistics
|
Buy Now
An Introduction to Bootstrap Methods with Applications to R (Hardcover)
Price: R1,885
Discovery Miles 18 850
|
|
|
An Introduction to Bootstrap Methods with Applications to R (Hardcover)
Expected to ship within 4 - 6 working days
|
A comprehensive introduction to bootstrap methods in the R
programming environment Bootstrap methods provide a powerful
approach to statistical data analysis, as they have more general
applications than standard parametric methods. An Introduction to
Bootstrap Methods with Applications to R explores the practicality
of this approach and successfully utilizes R to illustrate
applications for the bootstrap and other resampling methods. This
book provides a modern introduction to bootstrap methods for
readers who do not have an extensive background in advanced
mathematics. Emphasis throughout is on the use of bootstrap methods
as an exploratory tool, including its value in variable selection
and other modeling environments. The authors begin with a
description of bootstrap methods and its relationship to other
resampling methods, along with an overview of the wide variety of
applications of the approach. Subsequent chapters offer coverage of
improved confidence set estimation, estimation of error rates in
discriminant analysis, and applications to a wide variety of
hypothesis testing and estimation problems, including
pharmaceutical, genomics, and economics. To inform readers on the
limitations of the method, the book also exhibits counterexamples
to the consistency of bootstrap methods. An introduction to R
programming provides the needed preparation to work with the
numerous exercises and applications presented throughout the book.
A related website houses the book's R subroutines, and an extensive
listing of references provides resources for further study.
Discussing the topic at a remarkably practical and accessible
level, An Introduction to Bootstrap Methods with Applications to R
is an excellent book for introductory courses on bootstrap and
resampling methods at the upper-undergraduate and graduate levels.
It also serves as an insightful reference for practitioners working
with data in engineering, medicine, and the social sciences who
would like to acquire a basic understanding of bootstrap methods.
General
Is the information for this product incomplete, wrong or inappropriate?
Let us know about it.
Does this product have an incorrect or missing image?
Send us a new image.
Is this product missing categories?
Add more categories.
Review This Product
No reviews yet - be the first to create one!
|
|
Email address subscribed successfully.
A activation email has been sent to you.
Please click the link in that email to activate your subscription.