Description: Maximum Penalized Likelihood Estimation Please note: this item is printed on demand and will take extra time before it can be dispatched to you (up to 20 working days). Volume II: Regression Author(s): Paul P. Eggermont, Vincent N. LaRiccia Format: Paperback Publisher: Springer-Verlag New York Inc., United States Imprint: Springer-Verlag New York Inc. ISBN-13: 9781461417125, 978-1461417125 Synopsis 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
Number of Pages: 572 Pages
Publication Name: Maximum Penalized Likelihood Estimation: Volume Ii: Regression
Language: English
Publisher: Springer-Verlag New York Inc.
Item Height: 235 mm
Subject: Medicine, Economics, Engineering & Technology, Computer Science, Mathematics
Publication Year: 2011
Type: Textbook
Item Weight: 896 g
Author: Paul P. Eggermont, Vincent N. Lariccia
Item Width: 155 mm
Series: Springer Series in Statistics
Format: Paperback
