Description: Maximum Penalized Likelihood Estimation : Regression, Hardcover by Eggermont, P. P. B.; LaRiccia, V. N., ISBN 0387402675, ISBN-13 9780387402673, Like New Used, Free P&P in the UK
Unique blend of asymptotic theory and small sample practice through simulation experiments and data analysis.
Novel reproducing kernel Hilbert space methods for the analysis of smoothing splines and local polynomials. Leading to uniform error bounds and honest confidence bands for the mean function using smoothing splines
Exhaustive exposition of algorithms, including the Kalman filter, for the computation of smoothing splines of arbitrary order.
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Book Title: Maximum Penalized Likelihood Estimation : Regression
Number of Pages: 572 Pages
Language: English
Publication Name: Maximum Penalized Likelihood Estimation: Volume Ii: Regression
Publisher: Springer-Verlag New York Inc.
Publication Year: 2009
Subject: Medicine, Economics, Engineering & Technology, Computer Science, Mathematics
Item Height: 235 mm
Item Weight: 2210 g
Type: Textbook
Author: Paul P. Eggermont, Vincent N. Lariccia
Series: Springer Series in Statistics
Item Width: 155 mm
Format: Hardcover
