Nonparametric Function Estimation, Modeling, and Simulation
Published on 31. December 1990
Book
Paperback/Softback
320 pages
978-0-89871-261-2 (ISBN)
Description
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.
Special features include:
Concrete examples illustrate the theories presented.
Multi-dimensional problems are addressed.
A computer is used as an integral part of the modeling process.
Special features include:
Concrete examples illustrate the theories presented.
Multi-dimensional problems are addressed.
A computer is used as an integral part of the modeling process.
Reviews / Votes
'For those who do not have a copy of Tapia and Thompson (1978), the new book is definitely worth buying. The original Tapia and Thompson material in Chapters 1-5 is something everyone interested in density estimation should read, and the new chapters are a nice bonus....The newer material by Thompson contains thought-provoking treatments of some important issues that hopefully will provide a similar stimulus for research in its subject matter areas.' Randall L. Eubank, Journal of the American Statistical Association 'The authors share their experience with those who wish to use exploratory devices, such as nonparametric density estimation, towards a better understanding of real world processes, which require several characterizing parameters and have multidimensional data outputs. The book is reasonably successful in its attempt to be a 'road map' to investigators trying to make sense of the multiparametic models and multidimensional data ...The book makes for interesting reading and should help the reader avoid some of the false trails in analyzing multidimensional data, and perhaps spare the reader from repeating mistakes of the authors and others.' E. F. Schuster, Mathematical ReviewsMore details
Language
English
Place of publication
New York
United States
Target group
Professional and scholarly
Product notice
Paperback (trade)
Unsewn / adhesive bound
Dimensions
Height: 228 mm
Width: 152 mm
Thickness: 19 mm
Weight
445 gr
ISBN-13
978-0-89871-261-2 (9780898712612)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Content
Chapter 1: Historical Background
Chapter 2: Some Approaches to Nonparametric Density Estimation
Chapter 3: Maximum Likelihood Density Estimation
Chapter 4: Maximum Penalized Likelihood Density Estimation
Chapter 5: Discrete Maximum Penalized Likelihood Estimation
Chapter 6: Nonparametric Density of Estimation in Higher Dimensions
Chapter 7: Nonparametric Regression and Intensity Function Estimation
Chapter 8: Model Building and Speculative Data Analysis
Appendix I: An Introduction to Mathematical Optimization Theory
Appendix II: Numerical Solution of Constrained Optimization Problems
Appendix III: Optimization Algorithms for Noisy Problems
Appendix IV: A Brief Primer in Simulation
Index.
Chapter 2: Some Approaches to Nonparametric Density Estimation
Chapter 3: Maximum Likelihood Density Estimation
Chapter 4: Maximum Penalized Likelihood Density Estimation
Chapter 5: Discrete Maximum Penalized Likelihood Estimation
Chapter 6: Nonparametric Density of Estimation in Higher Dimensions
Chapter 7: Nonparametric Regression and Intensity Function Estimation
Chapter 8: Model Building and Speculative Data Analysis
Appendix I: An Introduction to Mathematical Optimization Theory
Appendix II: Numerical Solution of Constrained Optimization Problems
Appendix III: Optimization Algorithms for Noisy Problems
Appendix IV: A Brief Primer in Simulation
Index.