Author : Paul P. Eggermont
Publisher : Springer
Page : 0 pages
File Size : 31,35 MB
Release : 2011-12-02
Category : Mathematics
ISBN : 9781461417125
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.
Author : P.P.B. Eggermont
Publisher : Springer Nature
Page : 514 pages
File Size : 31,8 MB
Release : 2020-12-15
Category : Mathematics
ISBN : 1071612441
This book deals with parametric and nonparametric density estimation from the maximum (penalized) likelihood point of view, including estimation under constraints. The focal points are existence and uniqueness of the estimators, almost sure convergence rates for the L1 error, and data-driven smoothing parameter selection methods, including their practical performance. The reader will gain insight into technical tools from probability theory and applied mathematics.
Author : Paul P. Eggermont
Publisher : Springer Science & Business Media
Page : 580 pages
File Size : 10,3 MB
Release : 2009-06-02
Category : Mathematics
ISBN : 0387689028
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.
Author : Luc Duchateau
Publisher : Springer Science & Business Media
Page : 329 pages
File Size : 45,88 MB
Release : 2007-10-23
Category : Mathematics
ISBN : 038772835X
Readers will find in the pages of this book a treatment of the statistical analysis of clustered survival data. Such data are encountered in many scientific disciplines including human and veterinary medicine, biology, epidemiology, public health and demography. A typical example is the time to death in cancer patients, with patients clustered in hospitals. Frailty models provide a powerful tool to analyze clustered survival data. In this book different methods based on the frailty model are described and it is demonstrated how they can be used to analyze clustered survival data. All programs used for these examples are available on the Springer website.
Author : P.P.B. Eggermont
Publisher : Springer Science & Business Media
Page : 544 pages
File Size : 16,15 MB
Release : 2001-06-21
Category : Mathematics
ISBN : 9780387952680
This book deals with parametric and nonparametric density estimation from the maximum (penalized) likelihood point of view, including estimation under constraints. The focal points are existence and uniqueness of the estimators, almost sure convergence rates for the L1 error, and data-driven smoothing parameter selection methods, including their practical performance. The reader will gain insight into technical tools from probability theory and applied mathematics.
Author : Paulus Petrus Bernardus Eggermont
Publisher :
Page : pages
File Size : 13,38 MB
Release : 2001
Category : Estimation theory
ISBN :
Author : Jianguo Sun
Publisher : Springer
Page : 310 pages
File Size : 15,61 MB
Release : 2007-05-26
Category : Mathematics
ISBN : 0387371192
This book collects and unifies statistical models and methods that have been proposed for analyzing interval-censored failure time data. It provides the first comprehensive coverage of the topic of interval-censored data and complements the books on right-censored data. The focus of the book is on nonparametric and semiparametric inferences, but it also describes parametric and imputation approaches. This book provides an up-to-date reference for people who are conducting research on the analysis of interval-censored failure time data as well as for those who need to analyze interval-censored data to answer substantive questions.
Author : Michael R. Kosorok
Publisher : Springer Science & Business Media
Page : 482 pages
File Size : 13,8 MB
Release : 2007-12-29
Category : Mathematics
ISBN : 0387749780
Kosorok’s brilliant text provides a self-contained introduction to empirical processes and semiparametric inference. These powerful research techniques are surprisingly useful for developing methods of statistical inference for complex models and in understanding the properties of such methods. This is an authoritative text that covers all the bases, and also a friendly and gradual introduction to the area. The book can be used as research reference and textbook.
Author : Richard A. Tapia
Publisher :
Page : 196 pages
File Size : 48,8 MB
Release : 1978
Category : Mathematics
ISBN :
Author : James R. Thompson
Publisher : SIAM
Page : 320 pages
File Size : 44,25 MB
Release : 1990-01-01
Category : Mathematics
ISBN : 9781611971712
Topics emphasized include nonparametric density estimation as an exploratory device plus the deeper models to which the exploratory analysis points, multi-dimensional data analysis, and analysis of remote sensing data, cancer progression, chaos theory, epidemiological modeling, and parallel based algorithms. New methods discussed are quick nonparametric density estimation based techniques for resampling and simulation based estimation techniques not requiring closed form solutions.
