Nonparametric Estimation Of Change Points In Derivatives
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Change Point Problems
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Author : Edward G. Carlstein
language : en
Publisher: IMS
Release Date : 1994
Change Point Problems written by Edward G. Carlstein and has been published by IMS this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994 with Mathematics categories.
Artificial Intelligence And Soft Computing
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Author : Leszek Rutkowski
language : en
Publisher: Springer Nature
Release Date : 2020-10-20
Artificial Intelligence And Soft Computing written by Leszek Rutkowski and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-20 with Computers categories.
The two-volume set LNCS 12415 and 12416 constitutes the refereed proceedings of of the 19th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2020, held in Zakopane, Poland*, in October 2020. The 112 revised full papers presented were carefully reviewed and selected from 265 submissions. The papers included in the first volume are organized in the following six parts: neural networks and their applications; fuzzy systems and their applications; evolutionary algorithms and their applications; pattern classification; bioinformatics, biometrics and medical applications; artificial intelligence in modeling and simulation. The papers included in the second volume are organized in the following four parts: computer vision, image and speech analysis; data mining; various problems of artificial intelligence; agent systems, robotics and control. *The conference was held virtually due to the COVID-19 pandemic.
Nonparametric Estimation Of The P Th Derivative Of A Regression Function
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Author : I. A. Ahmad
language : en
Publisher: London : Department of Economics, University of Western Ontario
Release Date : 1988
Nonparametric Estimation Of The P Th Derivative Of A Regression Function written by I. A. Ahmad and has been published by London : Department of Economics, University of Western Ontario this book supported file pdf, txt, epub, kindle and other format this book has been release on 1988 with Econometrics categories.
Nonparametric Methods In Change Point Problems
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Author : E. Brodsky
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-14
Nonparametric Methods In Change Point Problems written by E. Brodsky and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-14 with Mathematics categories.
The explosive development of information science and technology puts in new problems involving statistical data analysis. These problems result from higher re quirements concerning the reliability of statistical decisions, the accuracy of math ematical models and the quality of control in complex systems. A new aspect of statistical analysis has emerged, closely connected with one of the basic questions of cynergetics: how to "compress" large volumes of experimental data in order to extract the most valuable information from data observed. De tection of large "homogeneous" segments of data enables one to identify "hidden" regularities in an object's behavior, to create mathematical models for each seg ment of homogeneity, to choose an appropriate control, etc. Statistical methods dealing with the detection of changes in the characteristics of random processes can be of great use in all these problems. These methods have accompanied the rapid growth in data beginning from the middle of our century. According to a tradition of more than thirty years, we call this sphere of statistical analysis the "theory of change-point detection. " During the last fifteen years, we have witnessed many exciting developments in the theory of change-point detection. New promising directions of research have emerged, and traditional trends have flourished anew. Despite this, most of the results are widely scattered in the literature and few monographs exist. A real need has arisen for up-to-date books which present an account of important current research trends, one of which is the theory of non parametric change--point detection.
Kernel Smoothing
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Author : Sucharita Ghosh
language : en
Publisher: John Wiley & Sons
Release Date : 2018-01-09
Kernel Smoothing written by Sucharita Ghosh and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-09 with Mathematics categories.
Comprehensive theoretical overview of kernel smoothing methods with motivating examples Kernel smoothing is a flexible nonparametric curve estimation method that is applicable when parametric descriptions of the data are not sufficiently adequate. This book explores theory and methods of kernel smoothing in a variety of contexts, considering independent and correlated data e.g. with short-memory and long-memory correlations, as well as non-Gaussian data that are transformations of latent Gaussian processes. These types of data occur in many fields of research, e.g. the natural and the environmental sciences, and others. Nonparametric density estimation, nonparametric and semiparametric regression, trend and surface estimation in particular for time series and spatial data and other topics such as rapid change points, robustness etc. are introduced alongside a study of their theoretical properties and optimality issues, such as consistency and bandwidth selection. Addressing a variety of topics, Kernel Smoothing: Principles, Methods and Applications offers a user-friendly presentation of the mathematical content so that the reader can directly implement the formulas using any appropriate software. The overall aim of the book is to describe the methods and their theoretical backgrounds, while maintaining an analytically simple approach and including motivating examples—making it extremely useful in many sciences such as geophysics, climate research, forestry, ecology, and other natural and life sciences, as well as in finance, sociology, and engineering. A simple and analytical description of kernel smoothing methods in various contexts Presents the basics as well as new developments Includes simulated and real data examples Kernel Smoothing: Principles, Methods and Applications is a textbook for senior undergraduate and graduate students in statistics, as well as a reference book for applied statisticians and advanced researchers.
Neural Information Processing
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Author : Haiqin Yang
language : en
Publisher: Springer Nature
Release Date : 2020-11-18
Neural Information Processing written by Haiqin Yang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-18 with Computers categories.
The two-volume set CCIS 1332 and 1333 constitutes thoroughly refereed contributions presented at the 27th International Conference on Neural Information Processing, ICONIP 2020, held in Bangkok, Thailand, in November 2020.* For ICONIP 2020 a total of 378 papers was carefully reviewed and selected for publication out of 618 submissions. The 191 papers included in this volume set were organized in topical sections as follows: data mining; healthcare analytics-improving healthcare outcomes using big data analytics; human activity recognition; image processing and computer vision; natural language processing; recommender systems; the 13th international workshop on artificial intelligence and cybersecurity; computational intelligence; machine learning; neural network models; robotics and control; and time series analysis. * The conference was held virtually due to the COVID-19 pandemic.
Nonparametric Statistical Methods And Related Topics
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Author : Francisco J. Samaniego
language : en
Publisher: World Scientific
Release Date : 2011-09-16
Nonparametric Statistical Methods And Related Topics written by Francisco J. Samaniego and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-09-16 with Mathematics categories.
This volume consists of 22 research papers by leading researchers in Probability and Statistics. Many of the papers are focused on themes that Professor Bhattacharya has published on research. Topics of special interest include nonparametric inference, nonparametric curve fitting, linear model theory, Bayesian nonparametrics, change point problems, time series analysis and asymptotic theory. This volume presents state-of-the-art research in statistical theory, with an emphasis on nonparametric inference, linear model theory, time series analysis and asymptotic theory. It will serve as a valuable reference to the statistics research community as well as to practitioners who utilize methodology in these areas of emphasis.
Estimations And Tests In Change Point Models
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Author : Pons Odile
language : en
Publisher: World Scientific
Release Date : 2018-05-28
Estimations And Tests In Change Point Models written by Pons Odile and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-28 with Mathematics categories.
This book provides a detailed exposition of the specific properties of methods of estimation and test in a wide range of models with changes. They include parametric and nonparametric models for samples, series, point processes and diffusion processes, with changes at the threshold of variables or at a time or an index of sampling. The book contains many new results and fills a gap in statistics literature, where the asymptotic properties of the estimators and test statistics in singular models are not sufficiently developed. It is suitable for graduate students and scientific researchers working in the industry, governmental laboratories and academia.
Recent Advances And Trends In Nonparametric Statistics
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Author : M.G. Akritas
language : en
Publisher: Elsevier
Release Date : 2003-10-31
Recent Advances And Trends In Nonparametric Statistics written by M.G. Akritas and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-10-31 with Mathematics categories.
The advent of high-speed, affordable computers in the last two decades has given a new boost to the nonparametric way of thinking. Classical nonparametric procedures, such as function smoothing, suddenly lost their abstract flavour as they became practically implementable. In addition, many previously unthinkable possibilities became mainstream; prime examples include the bootstrap and resampling methods, wavelets and nonlinear smoothers, graphical methods, data mining, bioinformatics, as well as the more recent algorithmic approaches such as bagging and boosting. This volume is a collection of short articles - most of which having a review component - describing the state-of-the art of Nonparametric Statistics at the beginning of a new millennium. Key features: • algorithic approaches • wavelets and nonlinear smoothers • graphical methods and data mining • biostatistics and bioinformatics • bagging and boosting • support vector machines • resampling methods
Functional Estimation For Density Regression Models And Processes Second Edition
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Author : Odile Pons
language : en
Publisher: World Scientific
Release Date : 2023-09-22
Functional Estimation For Density Regression Models And Processes Second Edition written by Odile Pons and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-22 with Mathematics categories.
Nonparametric kernel estimators apply to the statistical analysis of independent or dependent sequences of random variables and for samples of continuous or discrete processes. The optimization of these procedures is based on the choice of a bandwidth that minimizes an estimation error and the weak convergence of the estimators is proved. This book introduces new mathematical results on statistical methods for the density and regression functions presented in the mathematical literature and for functions defining more complex models such as the models for the intensity of point processes, for the drift and variance of auto-regressive diffusions and the single-index regression models.This second edition presents minimax properties with Lp risks, for a real p larger than one, and optimal convergence results for new kernel estimators of function defining processes: models for multidimensional variables, periodic intensities, estimators of the distribution functions of censored and truncated variables, estimation in frailty models, estimators for time dependent diffusions, for spatial diffusions and for diffusions with stochastic volatility.