Nonparametric Function Estimation, Modeling, and Simulation PDF Download

Author: James R. Thompson
Publisher: SIAM
ISBN: 9781611971712
Category : Mathematics
Languages : en
Pages : 320

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Book 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.

Author: James R. Thompson
Publisher: SIAM
ISBN: 0898712610
Category : Mathematics
Languages : en
Pages : 317

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Book Description
Topics emphasized in this book include nonparametric density estimation, multi-dimensional data analysis, cancer progression, chaos theory, and parallel based algorithms.

Author: G.G Roussas
Publisher: Springer Science & Business Media
ISBN: 9401132224
Category : Mathematics
Languages : en
Pages : 691

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Book Description
About three years ago, an idea was discussed among some colleagues in the Division of Statistics at the University of California, Davis, as to the possibility of holding an international conference, focusing exclusively on nonparametric curve estimation. The fruition of this idea came about with the enthusiastic support of this project by Luc Devroye of McGill University, Canada, and Peter Robinson of the London School of Economics, UK. The response of colleagues, contacted to ascertain interest in participation in such a conference, was gratifying and made the effort involved worthwhile. Devroye and Robinson, together with this editor and George Metakides of the University of Patras, Greece and of the European Economic Communities, Brussels, formed the International Organizing Committee for a two week long Advanced Study Institute (ASI) sponsored by the Scientific Affairs Division of the North Atlantic Treaty Organization (NATO). The ASI was held on the Greek Island of Spetses between July 29 and August 10, 1990. Nonparametric functional estimation is a central topic in statistics, with applications in numerous substantive fields in mathematics, natural and social sciences, engineering and medicine. While there has been interest in nonparametric functional estimation for many years, this has grown of late, owing to increasing availability of large data sets and the ability to process them by means of improved computing facilities, along with the ability to display the results by means of sophisticated graphical procedures.

Author: Yijia Feng
Publisher:
ISBN:
Category :
Languages : en
Pages : 137

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Author: Jiti Gao
Publisher: CRC Press
ISBN: 1420011219
Category : Mathematics
Languages : en
Pages : 249

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Book Description
Useful in the theoretical and empirical analysis of nonlinear time series data, semiparametric methods have received extensive attention in the economics and statistics communities over the past twenty years. Recent studies show that semiparametric methods and models may be applied to solve dimensionality reduction problems arising from using fully

Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 31

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Book Description
We compare parametric and nonparametric estimation methods in the context of PBPK modeling using simulation studies. We implement a Monte Carlo Markov Chain simulation technique in the parametric method, and a functional analytical approach to estimate the probability distribution function directly in the nonparametric method. The simulation results suggest an advantage for the parametric method when the underlying model can capture the true population distribution. On the other hand, our calculations demonstrate some advantages for a nonparametric approach since it is a more cautious (and hence safer) way to assess the distribution when one does not have sufficient knowledge to assume a population distribution form or parametrization. The parametric approach has obvious advantages when one has significant a priori information on the distributions sought, although when used in the nonparametric method, prior information can also significantly facilitate estimation.

Author: Alexandre B. Tsybakov
Publisher: Springer Science & Business Media
ISBN: 0387790527
Category : Mathematics
Languages : en
Pages : 222

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Book Description
Developed from lecture notes and ready to be used for a course on the graduate level, this concise text aims to introduce the fundamental concepts of nonparametric estimation theory while maintaining the exposition suitable for a first approach in the field.

Author: Richard A. Tapia
Publisher:
ISBN:
Category : Mathematics
Languages : en
Pages : 196

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Author: Zhibiao Zhao
Publisher:
ISBN:
Category :
Languages : en
Pages : 0

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Book Description
We study non-parametric regression function estimation for models with strong dependence. Compared with short-range dependent models, long-range dependent models often result in slower convergence rates. We propose a simple differencing-sequence based non-parametric estimator that achieves the same convergence rate as if the data were independent. Simulation studies show that the proposed method has good finite sample performance.

Author: Sam Efromovich
Publisher: Springer Science & Business Media
ISBN: 0387226389
Category : Mathematics
Languages : en
Pages : 423

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Book Description
This book gives a systematic, comprehensive, and unified account of modern nonparametric statistics of density estimation, nonparametric regression, filtering signals, and time series analysis. The companion software package, available over the Internet, brings all of the discussed topics into the realm of interactive research. Virtually every claim and development mentioned in the book is illustrated with graphs which are available for the reader to reproduce and modify, making the material fully transparent and allowing for complete interactivity.