FUNCTIONAL AND SHAPE DATA ANALYSIS
5,179.26₹ 6,474.00₹
- Author: ANUJ SRIVASTAVA
- ISBN: 9781493981557
- Availability: In Stock
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This textbook for courses on function data analysis and
shape data analysis describes how to define, compare, and mathematically
represent shapes, with a focus on statistical modeling and inference. It is
aimed at graduate students in analysis in statistics, engineering, applied
mathematics, neuroscience, biology, bioinformatics, and other related areas.
The interdisciplinary nature of the broad range of ideas covered—from
introductory theory to algorithmic implementations and some statistical case
studies—is meant to familiarize graduate students with an array of tools that
are relevant in developing computational solutions for shape and related
analyses. These tools, gleaned from geometry, algebra, statistics, and
computational science, are traditionally scattered across different courses,
departments, and disciplines; Functional
and Shape Data Analysis offers a unified, comprehensive solution by
integrating the registration problem into shape analysis, better preparing
graduate students for handling future scientific challenges.
Recently, a data-driven and application-oriented focus on
shape analysis has been trending. This text offers a self-contained treatment
of this new generation of methods in shape analysis of curves. Its main focus
is shape analysis of functions and curves—in one, two, and higher
dimensions—both closed and open. It develops elegant Riemannian frameworks that
provide both quantification of shape differences and registration of curves at
the same time. Additionally, these methods are used for statistically
summarizing given curve data, performing dimension reduction, and modeling
observed variability. It is recommended that the reader have a background in
calculus, linear algebra, numerical analysis, and computation.