Author: P.P.B. Eggermont
Publisher: Springer Nature
ISBN: 1071612441
Category : Mathematics
Languages : en
Pages : 514
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Book Description
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:
Publisher:
ISBN:
Category : Estimation theory
Languages : en
Pages : 0
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Book Description
Author: Paulus Petrus Bernardus Eggermont
Publisher:
ISBN:
Category : Estimation theory
Languages : en
Pages :
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Book Description
Author: P.P.B. Eggermont
Publisher: Springer
ISBN: 9780387952680
Category : Mathematics
Languages : en
Pages : 0
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Book Description
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
ISBN: 9781441929280
Category : Mathematics
Languages : en
Pages : 512
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Book Description
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
ISBN: 9780387952680
Category : Mathematics
Languages : en
Pages : 512
Get Book
Book Description
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
ISBN: 9780387952680
Category : Mathematics
Languages : en
Pages : 512
Get Book
Book Description
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
ISBN: 0387689028
Category : Mathematics
Languages : en
Pages : 580
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Book Description
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
ISBN: 038772835X
Category : Mathematics
Languages : en
Pages : 316
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Book Description
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: Shihong Yu
Publisher:
ISBN:
Category : Iterative methods (Mathematics)
Languages : en
Pages : 17
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Book Description
