aam a22 4500
212008
212008
190501b 2017 ||||| |||| 00| 0 eng d
9781498746342
515.7
K6I6
Kokoszka, Piotr
379330
Introduction to functional data analysis
CRC Press
2017
Florida
xvi, 290p.
With index
Chapman & Hall/CRC texts in statistical series
379331
Table of Contents
1 First steps in the analysis of functional data
2 Further topics in exploratory FDA
3 Mathematical framework for functional data
4 Scalar- on - function regression
5 Functional response models
6 Functional generalized linear models
7 Sparse FDA
8 Functional time series
9 Spatial functional data and models
10 Elements of Hilbert space theory
11 Random functions
12 Inference from a random sample
Introduction to Functional Data Analysis provides a concise textbook introduction to the field. It explains how to analyze functional data, both at exploratory and inferential levels. It also provides a systematic and accessible exposition of the methodology and the required mathematical framework. The book can be used as textbook for a semester-long course on FDA for advanced undergraduate or MS statistics majors, as well as for MS and PhD students in other disciplines, including applied mathematics, environmental science, public health, medical research, geophysical sciences and economics. It can also be used for self-study and as a reference for researchers in those fields who wish to acquire solid understanding of FDA methodology and practical guidance for its implementation. Each chapter contains plentiful examples of relevant R code and theoretical and data analytic problems. The material of the book can be roughly divided into four parts of approximately equal length: 1) basic concepts and techniques of FDA, 2) functional regression models, 3) sparse and dependent functional data, and 4) introduction to the Hilbert space framework of FDA. The book assumes advanced undergraduate background in calculus, linear algebra, distributional probability theory, foundations of statistical inference, and some familiarity with R programming. Other required statistics background is provided in scalar settings before the related functional concepts are developed. Most chapters end with references to more advanced research for those who wish to gain a more in-depth understanding of a specific topic.
https://www.crcpress.com/Introduction-to-Functional-Data-Analysis/Kokoszka-Reimherr/p/book/9781498746342
Functional analysis
379332
Probability theory and applications
379333
Statistical theory and methods
379334
Reimherr, Matthew
Co author
379335
ddc
BK
0
0
ddc
0
515_700000000000000_K6I6
0
NFIC
358380
VSL
VSL
GEN
2019-04-30
12
4.00
Slot 1365 (0 Floor, East Wing)
515.7 K6I6
199254
2019-04-30
5830.64
BK