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Statistics 526 Term 2 2005-6
Smoothing Methods/Functional Data Analysis
BOOKS
The following books are on reserve for this course.
Applied functional data analysis : methods and case studies
J.O. Ramsay, B.W. Silverman.
MATHEMATICS LIBRARY QA278 .R35 2002
Functional data analysis
J.O. Ramsay, B.W. Silverman
MAIN LIBRARY QA278 .R36 2005
(new edition of their older book)
Generalized additive models
T.J. Hastie, R.J. Tibshirani
MATHEMATICS LIBRARY QA276 .H377 1990
The first few chapters give a very nice qualitative overview
of smoothing.
Kernel smoothing
M.P. Wand, M.C. Jones
MATHEMATICS LIBRARY QA297.6 .W36 1995
Local polynomial modelling and its applications
J. Fan and I. Gijbels
MATHEMATICS LIBRARY QA278.2 .F36 1996
Local regression and likelihood
Clive Loader
MAIN LIBRARY QA276.8 .L6 1999
There is an R package to go with this: locfit.
Nonparametric regression and spline smoothing
Randall L. Eubank.
MAIN LIBRARY QA278.2 .E93 1999
and an earlier version:
MAIN LIBRARY QA278.2 .E93 1988
The early version gave a very balanced view of different methods
of smoothing. The material was presented in good detail, at
a reasonable level for graduate students. However, now the material
is a little dated. I haven't seen the
new edition.
Smoothing methods in statistics
Jeffrey S. Simonoff
MATHEMATICS LIBRARY QA278 .S526 1996
Nice balanced view of smoothing with an emphasis on applications.
Not a lot of detail, but a good overview.
NOT ON RESERVE
Spline models for observational data
Grace Wahba
MATHEMATICS LIBRARY QA224 .W34 1987
Very technical, high math level, but very good.
Smoothing spline ANOVA models
Chong Gu
MAIN LIBRARY QA279 .G8 2002
Contains much of the material in Wahba, but updated and
expanded, with many new results. Chong has an R package,
gss.
Semiparametric regression
David Ruppert, M.P. Wand, R.J. Carroll.
MATHEMATICS LIBRARY QA278.2 .R87 2003
Gives a nice overview of smoothing methods, then focusses on penalized regression, mixed effects/Bayes modelling, and
semiparametric regression.
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