Estimation Yield Curves by Kernel Smoothing Methods PDF Download
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Author: O. Linton
Publisher:
ISBN:
Category :
Languages : en
Pages : 54
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Book Description
Author: O. Linton
Publisher:
ISBN:
Category :
Languages : en
Pages : 54
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Book Description
Author: Oliver B. Linton
Publisher:
ISBN:
Category : Government securities
Languages : en
Pages : 42
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Book Description
Author: Oliver Linton
Publisher:
ISBN:
Category :
Languages : en
Pages : 54
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Book Description
Author: Oliver Linton
Publisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 0
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Book Description
Author: Sucharita Ghosh
Publisher: John Wiley & Sons
ISBN: 111845605X
Category : Mathematics
Languages : en
Pages : 272
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Book Description
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.
Author: M.P. Wand
Publisher: CRC Press
ISBN: 9780412552700
Category : Mathematics
Languages : en
Pages : 230
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Book Description
Kernel smoothing refers to a general methodology for recovery of underlying structure in data sets. The basic principle is that local averaging or smoothing is performed with respect to a kernel function. This book provides uninitiated readers with a feeling for the principles, applications, and analysis of kernel smoothers. This is facilitated by the authors' focus on the simplest settings, namely density estimation and nonparametric regression. They pay particular attention to the problem of choosing the smoothing parameter of a kernel smoother, and also treat the multivariate case in detail. Kernal Smoothing is self-contained and assumes only a basic knowledge of statistics, calculus, and matrix algebra. It is an invaluable introduction to the main ideas of kernel estimation for students and researchers from other discipline and provides a comprehensive reference for those familiar with the topic.
Author: Ivanka Horova
Publisher: World Scientific
ISBN: 9814405493
Category : Mathematics
Languages : en
Pages : 242
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Book Description
Methods of kernel estimates represent one of the most effective nonparametric smoothing techniques. These methods are simple to understand and they possess very good statistical properties. This book provides a concise and comprehensive overview of statistical theory and in addition, emphasis is given to the implementation of presented methods in Matlab. All created programs are included in a special toolbox which is an integral part of the book. This toolbox contains many Matlab scripts useful for kernel smoothing of density, cumulative distribution function, regression function, hazard function, indices of quality and bivariate density. Specifically, methods for choosing a choice of the optimal bandwidth and a special procedure for simultaneous choice of the bandwidth, the kernel and its order are implemented. The toolbox is divided into six parts according to the chapters of the book.All scripts are included in a user interface and it is easy to manipulate with this interface. Each chapter of the book contains a detailed help for the related part of the toolbox too. This book is intended for newcomers to the field of smoothing techniques and would also be appropriate for a wide audience: advanced graduate, PhD students and researchers from both the statistical science and interface disciplines.
Author: M.G. Akritas
Publisher: Elsevier
ISBN: 0444513787
Category : Computers
Languages : en
Pages : 524
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Book Description
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
Author: Nicola Anderson
Publisher:
ISBN:
Category : Business & Economics
Languages : en
Pages : 248
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Book Description
A yield curve is a graph indicating the term structure of interest rates by plotting the yields of all bonds of the same quality. This book provides a thorough analysis of estimation techniques and a survey of yield curve interpretation. On the former it is the most advanced book in its field, on the latter it provides an introduction to more specialised texts. It also provides important insight into the latest thinking on these techniques at the Bank of England.
Author: Jeffrey Racine
Publisher: Oxford University Press
ISBN: 0199857946
Category : Business & Economics
Languages : en
Pages : 562
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Book Description
This volume, edited by Jeffrey Racine, Liangjun Su, and Aman Ullah, contains the latest research on nonparametric and semiparametric econometrics and statistics. Chapters by leading international econometricians and statisticians highlight the interface between econometrics and statistical methods for nonparametric and semiparametric procedures.
