UID:
almafu_9959244708602883
Format:
1 online resource (xvi, 386 pages) :
,
digital, PDF file(s).
ISBN:
1-107-12902-8
,
0-511-06683-X
,
1-280-41790-0
,
9786610417902
,
0-511-17948-0
,
0-511-20343-8
,
0-511-75545-7
,
0-511-32379-4
,
0-511-06896-4
Series Statement:
Cambridge series in statistical and probabilistic mathematics
Content:
Assuming only a basic familiarity with ordinary parametric regression, this user-friendly book explains the techniques and benefits of semiparametric regression in a concise and modular fashion. The authors make liberal use of graphics and examples plus case studies taken from environmental, financial, and other applications. They include practical advice on implementation and pointers to relevant software.
Note:
Description based upon print version of record.
,
Cover; Half-title; Series-title; Title; Copyright; Dedication; Contents; Preface; Guide to Notation; 1 Introduction; 2 Parametric Regression; 3 Scatterplot Smoothing; 4 Mixed Models; 5 Automatic Scatterplot Smoothing; 6 Inference; 7 Simple Semiparametric Models; 8 Additive Models; 9 Semiparametric Mixed Models; 10 Generalized Parametric Regression; 11 Generalized Additive Models; 12 Interaction Models; 13 Bivariate Smoothing; 14 Variance Function Estimation; 15 Measurement Error; 16 Bayesian Semiparametric Regression; 17 Spatially Adaptive Smoothing; 18 Analyses; 19 Epilogue
,
A Technical ComplementsB Computational Issues; Bibliography; Author Index; Notation Index; Example Index; Subject Index
,
English
Additional Edition:
ISBN 0-521-78516-2
Additional Edition:
ISBN 0-521-78050-0
Language:
English
URL:
https://doi.org/10.1017/CBO9780511755453
URL:
https://doi.org/10.1017/CBO9780511755453
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