Maximum Penalized Likelihood Estimation
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Author |
: Paul P. Eggermont |
Publisher |
: Springer Science & Business Media |
Total Pages |
: 580 |
Release |
: 2009-06-02 |
ISBN-10 |
: 9780387689029 |
ISBN-13 |
: 0387689028 |
Rating |
: 4/5 (29 Downloads) |
Synopsis Maximum Penalized Likelihood Estimation by : Paul P. Eggermont
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 |
Total Pages |
: 514 |
Release |
: 2020-12-15 |
ISBN-10 |
: 9781071612446 |
ISBN-13 |
: 1071612441 |
Rating |
: 4/5 (46 Downloads) |
Synopsis Maximum Penalized Likelihood Estimation by : P.P.B. Eggermont
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 |
: |
Total Pages |
: |
Release |
: 2001 |
ISBN-10 |
: LCCN:2001020450 |
ISBN-13 |
: |
Rating |
: 4/5 (50 Downloads) |
Synopsis Maximum Penalized Likelihood Estimation: Regression by : Paulus Petrus Bernardus Eggermont
Author |
: P.P.B. Eggermont |
Publisher |
: Springer |
Total Pages |
: 0 |
Release |
: 2001-06-21 |
ISBN-10 |
: 0387952683 |
ISBN-13 |
: 9780387952680 |
Rating |
: 4/5 (83 Downloads) |
Synopsis Maximum Penalized Likelihood Estimation by : P.P.B. Eggermont
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 |
: Tyler Shumway |
Publisher |
: |
Total Pages |
: 32 |
Release |
: 1991 |
ISBN-10 |
: OCLC:367364674 |
ISBN-13 |
: |
Rating |
: 4/5 (74 Downloads) |
Synopsis Adaptive Maximum Penalized Likelihood Estimation by : Tyler Shumway
Author |
: P.P.B. Eggermont |
Publisher |
: Springer |
Total Pages |
: 512 |
Release |
: 2001-06-21 |
ISBN-10 |
: 0387952683 |
ISBN-13 |
: 9780387952680 |
Rating |
: 4/5 (83 Downloads) |
Synopsis Maximum Penalized Likelihood Estimation by : P.P.B. Eggermont
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 |
: P.P.B. Eggermont |
Publisher |
: Springer |
Total Pages |
: 512 |
Release |
: 2001-06-21 |
ISBN-10 |
: 0387952683 |
ISBN-13 |
: 9780387952680 |
Rating |
: 4/5 (83 Downloads) |
Synopsis Maximum Penalized Likelihood Estimation by : P.P.B. Eggermont
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 |
: Shih-hung Yü |
Publisher |
: |
Total Pages |
: 206 |
Release |
: 1997 |
ISBN-10 |
: OCLC:223010380 |
ISBN-13 |
: |
Rating |
: 4/5 (80 Downloads) |
Synopsis Maximum Penalized Likelihood Estimation by : Shih-hung Yü
Author |
: André Michelle Lubecke |
Publisher |
: |
Total Pages |
: 140 |
Release |
: 1985 |
ISBN-10 |
: OCLC:16799783 |
ISBN-13 |
: |
Rating |
: 4/5 (83 Downloads) |
Synopsis Nonparametric Maximum Penalized Likelihood Estimation of Lifetime Density Functions by : André Michelle Lubecke
Author |
: Luc Duchateau |
Publisher |
: Springer Science & Business Media |
Total Pages |
: 329 |
Release |
: 2007-10-23 |
ISBN-10 |
: 9780387728353 |
ISBN-13 |
: 038772835X |
Rating |
: 4/5 (53 Downloads) |
Synopsis The Frailty Model by : Luc Duchateau
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.