Nonparametric Regression and Spline Smoothing
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A01=Randall L. Eubank
advanced regression techniques
asymptotic analysis
Author_Randall L. Eubank
Bayesian Confidence Intervals
Bonferroni Intervals
Boundary Kernels
Category=PBK
Category=PBT
cauchy
confidence bands
Cosine Series
Cubic Splines
Data Set
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
Estimated Fourier Coefficients
estimator
estimators
function
goodness-of-fit testing in nonparametric models
Interval Estimators
kernel
Kernel Estimators
linear
Linear Estimators
Local Linear Regression Estimator
Nonparametric Regression
partially linear models
polynomial
Polynomial Regression
Polynomial Regression Estimators
Quadratic Kernel
Quadratic Splines
Regression Function
Ridge Estimators
risk
Series Estimator
Smoothing Parameter
Smoothing Spline Estimator
Smoothing Spline Fit
statistical learning
trigonometric series methods
true
True Regression Function
Truncated Power Basis
unbiased
Unknown Regression Function
Product details
- ISBN 9780824793371
- Weight: 660g
- Dimensions: 156 x 234mm
- Publication Date: 09 Feb 1999
- Publisher: Taylor & Francis Inc
- Publication City/Country: US
- Product Form: Hardback
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Provides a unified account of the most popular approaches to nonparametric regression smoothing. This edition contains discussions of boundary corrections for trigonometric series estimators; detailed asymptotics for polynomial regression; testing goodness-of-fit; estimation in partially linear models; practical aspects, problems and methods for confidence intervals and bands; local polynomial regression; and form and asymptotic properties of linear smoothing splines.
Randall L. Eubank
