Books > Science & Mathematics > Mathematics > Probability & statistics
|
Buy Now
Nonparametric Models for Longitudinal Data - With Implementation in R (Paperback)
Loot Price: R1,834
Discovery Miles 18 340
|
|
Nonparametric Models for Longitudinal Data - With Implementation in R (Paperback)
Series: Chapman & Hall/CRC Monographs on Statistics and Applied Probability
Expected to ship within 9 - 15 working days
|
Nonparametric Models for Longitudinal Data with Implementations in
R presents a comprehensive summary of major advances in
nonparametric models and smoothing methods with longitudinal data.
It covers methods, theories, and applications that are particularly
useful for biomedical studies in the era of big data and precision
medicine. It also provides flexible tools to describe the temporal
trends, covariate effects and correlation structures of repeated
measurements in longitudinal data. This book is intended for
graduate students in statistics, data scientists and statisticians
in biomedical sciences and public health. As experts in this area,
the authors present extensive materials that are balanced between
theoretical and practical topics. The statistical applications in
real-life examples lead into meaningful interpretations and
inferences. Features: Provides an overview of parametric and
semiparametric methods Shows smoothing methods for unstructured
nonparametric models Covers structured nonparametric models with
time-varying coefficients Discusses nonparametric shared-parameter
and mixed-effects models Presents nonparametric models for
conditional distributions and functionals Illustrates
implementations using R software packages Includes datasets and
code in the authors' website Contains asymptotic results and
theoretical derivations Both authors are mathematical statisticians
at the National Institutes of Health (NIH) and have published
extensively in statistical and biomedical journals. Colin O. Wu
earned his Ph.D. in statistics from the University of California,
Berkeley (1990), and is also Adjunct Professor at the Georgetown
University School of Medicine. He served as Associate Editor for
Biometrics and Statistics in Medicine, and reviewer for National
Science Foundation, NIH, and the U.S. Department of Veterans
Affairs. Xin Tian earned her Ph.D. in statistics from Rutgers, the
State University of New Jersey (2003). She has served on various
NIH committees and collaborated extensively with clinical
researchers.
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!
|
You might also like..
|
Email address subscribed successfully.
A activation email has been sent to you.
Please click the link in that email to activate your subscription.