# Nonparametric Functional Data Analysis: Theory And Practice

@article{Lu2007NonparametricFD, title={Nonparametric Functional Data Analysis: Theory And Practice}, author={Z. Q. John Lu}, journal={Technometrics}, year={2007}, volume={49}, pages={226 - 226} }

This is a research monograph rather than a practical book or, even less, a textbook. For the latter, your needs are better served by Ramsay and Silverman (2005a, b). In a sense, the present book is heavily biased toward statistical theory and is weak on practice and applications. For the theory aspect, the present book does bring something new and, indeed, some novel theoretical investigations into the kinds of functional data problems not addressed by Ramsay and Silverman (2005a). While Ramsay…

## Topics from this paper

## 818 Citations

Functional Data Smoothing Methods and Their Applications

- Computer Science
- 2017

This dissertation showed that using the Bayesian smoothing method on the raw curves prior to carrying out the corresponding applications provides very competitive statistical inference and an- it is proved to adapt more flexibly to highly irregular curves.

The bbefkr Package

- 2014

Recent advances in computer recording and storing technology have markedly increased the presence of functional data, whose graphical representation can be infinite-dimensional curve, image or shape.…

Robust Statistical Methods for the Functional Logistic Model by Melody B. Denhere

- 2013

Over the last decade or so, a lot of interest has emerged in the field of functional data analysis. This interest spans from a broad spectrum of fields such as brain imaging studies, bio-metrics,…

Principal differential analysis with a continuous covariate: low-dimensional approximations for functional data

- Mathematics, MedicineJournal of statistical computation and simulation
- 2013

PDA is useful for obtaining low-dimensional approximations to the data curves whether or not the interpretation of the annihilating LDO is intuitive or obvious from the context of the data.

Single and multiple index functional regression models with nonparametric link

- Mathematics
- 2011

Fully nonparametric methods for regression from functional data have poor accuracy
from a statistical viewpoint, reflecting the fact that their convergence rates are slower
than nonparametric rates…

ON THE VALIDITY OF THE BOOTSTRAP IN NONPARAMETRIC FUNCTIONAL REGRESSION

- 2008

We consider the functional nonparametric regression model Y = r(X)+", where the response Y is univariate, X is a functional covariate (i.e. valued in some infinite-dimensional space), and the error "…

AN INTRODUCTION TO THEORETICAL PROPERTIES OF FUNCTIONAL PRINCIPAL COMPONENT ANALYSIS

- 2008

The term “functional data” refers to data where each observation is a curve, a surface, or a hypersurface, as opposed to a point or a finite-dimensional vector. Functional data are intrinsically…

Bootstrap and inference when both response and regressor are functional

- Mathematics
- 2010

We consider a nonparametric regression model where the response Y and the covariate X are both functional (i.e. valued in some infinite-dimensional space). We define a kernel type estimator of the…

Regression when both response and predictor are functions

- Computer Science, MathematicsJ. Multivar. Anal.
- 2012

The theoretical advances are completed by some simulation studies showing both the practical feasibility of the method and the good behavior for finite sample sizes of the kernel estimator and of the bootstrap procedures to build functional pseudo-confidence area.

Peter Hall, functional data analysis and random objects

- Mathematics
- 2016

Functional data analysis has become a major branch of nonparametric statistics and is a fast evolving field. Peter Hall has made fundamental contributions to this area and its theoretical…

## References

SHOWING 1-2 OF 2 REFERENCES

Nonparametric Regression with Singular Design

- Mathematics
- 1999

Theories of nonparametric regression are usually based on the assumption that the design density exists. However, in some applications such as those involving high-dimensional or chaotic time series…

Functional Data Analysis (2nd ed.), New York: Springer-Verlag. (2005b), Applied Functional Data Analysis, New York: SpringerVerlag

- 2005