6 edition of **Nonparametric Functional Estimation and Related Topics** found in the catalog.

- 31 Want to read
- 8 Currently reading

Published
**April 30, 1991**
by Springer
.

Written in English

- Science/Mathematics,
- Mathematical Statistics,
- Mathematics,
- Probability & Statistics - General,
- Mathematics / Statistics,
- Congresses,
- Estimation theory,
- Nonparametric statistics

**Edition Notes**

NATO Science Series C: (closed)

The Physical Object | |
---|---|

Format | Hardcover |

Number of Pages | 728 |

ID Numbers | |

Open Library | OL7806597M |

ISBN 10 | 0792312260 |

ISBN 10 | 9780792312260 |

given different treatments) and for two related samples (for example, before-and-after measurements on a single group of subjects). Related samples are also referred to as paired samples or matched pairs. Comparing Two Independent Samples SAS/STAT software provides several nonparametric tests for location and scale differences for two inde-. methods. But it is hard to ﬁnd all these topics covered in one place. The goal of this text is to provide readers with a single book where they can ﬁnd a brief account of many of the modern topics in nonparametric inference. The book is aimed at master’s-level or Ph.D.-level statistics and computer science students.

1.A. Nemirovski. \Topics in non-parametric Statistics." Ecole d’Ete de Probabilites de Saint-Flour 28 (): 2.A.B. Tsybakov. \Introduction to Nonparametric Estimation." Springer, 2 The Bias{Variance Decomposition Before looking at speci c function class Fand estimators f^, we take a look at how to evaluate the performance. Nonparametric Functional Estimation and Related Topics, () Non-parametric estimation of conditional quantiles. Statistics & Probability Letters , Cited by:

Nonparametric Estimation for Functional Data by Wavelet Thresholding 1. INTRODUCTION Due to technological progress, in particular the enlarged capacity of com-puter memory and the increasing eﬃciency of data collection devices, there is a growing number of applied sciences (biometrics, chemometrics, meteorology,Cited by: 1. Preface This work is the fruit of recent advances concerning both nonparametric sta-tistical modelling and functional variables and is based on various publica-File Size: 96KB.

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The ASI was held on the Greek Island of Spetses between July 29 and Aug Nonparametric functional estimation is a central topic in statistics, with applications in numerous substantive fields in mathematics, natural and social sciences, engineering and medicine. Nonparametric Functional Estimation is a compendium of papers, written by experts, in the area of nonparametric functional estimation.

This book attempts to be exhaustive in nature and is written both for specialists in the area as well as for students of statistics taking courses at Book Edition: 1. 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 Format: Hardcover. ISBN: OCLC Number: Notes: "Proceedings of the NATO Advanced Study Institute on Nonparametric Functional Estimation and Related Topics, Spetses, Greece, July Aug "--Title page verso.

Nonparametric Functional Estimation is a compendium of papers, written by experts, in the area of nonparametric functional estimation. This book attempts to be exhaustive in nature and is written both for specialists in the area as well as for students of statistics taking courses at the postgraduate level.

The main emphasis throughout the book. COVID Resources. Reliable information about the coronavirus (COVID) is available from the World Health Organization (current situation, international travel).Numerous and frequently-updated resource results are available from this ’s WebJunction has pulled together information and resources to assist library staff as they consider how to handle coronavirus.

Nonparametric estimation of the conditional occupation probability distributions for the different states in multistate networks with multiple covariates is a relatively unexplored area of research.

Past studies related to multistate models have mostly delved upon specific parametric/semiparametric models on the hazards of transitions from one. Applied Nonparametric Regression is the first book to bring together in one place the techniques for regression curve smoothing involving more than one variable.

The computer and the development of interactive graphics programs have made curve estimation by: Topics of special interest include nonparametric inference, nonparametric curve fitting, linear model theory, Bayesian nonparametrics, change point problems, time series analysis and asymptotic volume presents state-of-the-art research in statistical theory, with an emphasis on nonparametric inference, linear model theory, time Author: Francisco J Samaniego.

Nonparametric Statistical Methods and Related Topics. Topics of special interest include nonparametric inference, nonparametric curve fitting, linear model theory, Bayesian nonparametrics, change point problems, time series analysis and asymptotic theory. Density Estimation by Sampling from Stationary Continuous Time Parameter.

Professor Puri is one of the most versatile and prolific researchers in the world in mathematical statistics. His research areas include nonparametric statistics, order statistics, limit theory under mixing, time series, splines, tests of normality, generalized inverses of matrices and related topics, stochastic processes, statistics of directional data, random sets, and fuzzy sets and fuzzy.

Härdle W., Mammen E. () Bootstrap Methods in Nonparametric Regression. In: Roussas G. (eds) Nonparametric Functional Estimation and Related Topics. NATO ASI Series (Series C: Mathematical and Physical Sciences), vol Cited by: Topics include the bootstrap, smoothing techniques, density estimation, regression, and lots of other things.

No nonparametric Bayes, however. $\endgroup$ – guy Mar 4 '13 at $\begingroup$ I have checked that one out but its more like a reference book than learning material. Chapter 9 Nonparametric Function Estimation 1. Nonparametric models and parameters 2. Kernel estimation of densities 3.

Other density estimation methods 4. (Minimax) Rates of convergence more generally 5. Nonparametric estimation of regression functions 6.

Estimation of smooth functionals of densities 7. Shape constrained estimation Size: KB. Topics in Non-Parametric Statistics Arkadi Nemirovski1 Preface The subject of Nonparametric statistics is statistical inference applied to noisy obser-vations of inﬂnite-dimensional \parameters" like images and time-dependent signals.

This is a mathematical area on File Size: 3MB. This book will introduce various types of data encountered in practice and suggest the appropriate nonparametric methods, discuss their properties through null and non-null distributions whenever possible and demonstrate the very minor loss in power and efficiency in the nonparametric method, if any.

The book will cover almost all topics of. The nonparametric estimation of the functional regression was initially studied by Ferraty and Vieu () with is a kernel function and is a nonnegative real sequence. () Nonparametric estimation of variance function for functional data under mixing conditions.

Communications in Statistics – Theory and Meth – Jones, by: 5. A linear combination of a parametric and a nonparametric estimate of an unknown regression function is considered as a hybrid estimate.

The technique can be viewed as a functional version of the famous James–Stein approach used in parameter estimation. Organized a high profile two-week (July Aug ) NATO-sponsored workshop in the island of Spetses, Greece, and singlehandedly edited a page volume of contributed papers (Nonparametric Functional Estimation and Related Topics, Kluwer Academic Publishers, ).

Nonparametric Estimation for Functional Data by Wavelet Thresholding. Recent Advances in Functional Data Analysis and Related Topics. Nonparametric Estimation in Functional Linear Model.From the reviews: “Topics are useful, interesting, and related to the hot area of high-dimensional data analysis.

I think the volume will draw attention from researchers as well as practitioners involved in the areas of functional data, high-dimensional data and spatial functional data, and related topics.

.It covers a wide range of topics including the bootstrap, the nonparametric delta method, nonparametric regression, density estimation, orthogonal function methods, minimax estimation, nonparametric confidence sets, and wavelets. The book’s dual approach includes a mixture of methodology and theory.