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Author: Kung-Sik Chan
Publisher: Springer Science & Business Media
ISBN: 1475734646
Category : Mathematics
Languages : en
Pages : 312
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Book Description
This book discusses dynamical systems that are typically driven by stochastic dynamic noise. It is written by two statisticians essentially for the statistically inclined readers. It covers many of the contributions made by the statisticians in the past twenty years or so towards our understanding of estimation, the Lyapunov-like index, the nonparametric regression, and many others, many of which are motivated by their dynamical system counterparts but have now acquired a distinct statistical flavor.
Author: Kung-Sik Chan
Publisher: Springer Science & Business Media
ISBN: 1475734646
Category : Mathematics
Languages : en
Pages : 312
Get Book Here
Book Description
This book discusses dynamical systems that are typically driven by stochastic dynamic noise. It is written by two statisticians essentially for the statistically inclined readers. It covers many of the contributions made by the statisticians in the past twenty years or so towards our understanding of estimation, the Lyapunov-like index, the nonparametric regression, and many others, many of which are motivated by their dynamical system counterparts but have now acquired a distinct statistical flavor.
Author: C. Benton
Publisher: BoD – Books on Demand
ISBN: 3385607620
Category : Fiction
Languages : en
Pages : 150
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Book Description
Reprint of the original, first published in 1837.
Author:
Publisher:
ISBN:
Category : Sheep
Languages : en
Pages : 166
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Book Description
Author: Jesse Chickering
Publisher:
ISBN:
Category : Mathematics
Languages : en
Pages : 270
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Book Description
Author: Maarten Jansen
Publisher: CRC Press
ISBN: 1000564177
Category : Business & Economics
Languages : en
Pages : 474
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Book Description
Wavelets from a Statistical Perspective offers a modern, 2nd generation look on wavelets, far beyond the rigid setting of the equispaced, dyadic wavelets in the early days. With the methods of this book, based on the lifting scheme, researchers can set up a wavelet or another multiresolution analysis adapted to their data, ranging from images to scattered data or other irregularly spaced observations. Whereas classical wavelets stand a bit apart from other nonparametric methods, this book adds a multiscale touch to your spline, kernel or local polynomial smoothing procedure, thereby extending its applicability to nonlinear, nonparametric processing for piecewise smooth data. One of the chapters of the book constructs B-spline wavelets on nonequispaced knots and multiscale local polynomial transforms. In another chapter, the link between wavelets and Fourier analysis, ubiquitous in the classical approach, is explained, but without being inevitable. In further chapters the discrete wavelet transform is contrasted with the continuous version, the nondecimated (or maximal overlap) transform taking an intermediate position. An important principle in designing a wavelet analysis through the lifting scheme is finding the right balance between bias and variance. Bias and variance also play a crucial role in the nonparametric smoothing in a wavelet framework, in finding well working thresholds or other smoothing parameters. The numerous illustrations can be reproduced with the online available, accompanying software. The software and the exercises can also be used as a starting point in the further exploration of the material.
Author: De_Bow (J. D. B.)
Publisher:
ISBN:
Category : United States
Languages : en
Pages : 410
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Book Description
Author: Gareth James
Publisher: Springer Nature
ISBN: 3031387473
Category : Mathematics
Languages : en
Pages : 617
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Book Description
An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance, marketing, and astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. This book is targeted at statisticians and non-statisticians alike, who wish to use cutting-edge statistical learning techniques to analyze their data. Four of the authors co-wrote An Introduction to Statistical Learning, With Applications in R (ISLR), which has become a mainstay of undergraduate and graduate classrooms worldwide, as well as an important reference book for data scientists. One of the keys to its success was that each chapter contains a tutorial on implementing the analyses and methods presented in the R scientific computing environment. However, in recent years Python has become a popular language for data science, and there has been increasing demand for a Python-based alternative to ISLR. Hence, this book (ISLP) covers the same materials as ISLR but with labs implemented in Python. These labs will be useful both for Python novices, as well as experienced users.
Author: Daniel Navarro
Publisher: Lulu.com
ISBN: 1326189727
Category : Computers
Languages : en
Pages : 617
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Book Description
"Learning Statistics with R" covers the contents of an introductory statistics class, as typically taught to undergraduate psychology students, focusing on the use of the R statistical software and adopting a light, conversational style throughout. The book discusses how to get started in R, and gives an introduction to data manipulation and writing scripts. From a statistical perspective, the book discusses descriptive statistics and graphing first, followed by chapters on probability theory, sampling and estimation, and null hypothesis testing. After introducing the theory, the book covers the analysis of contingency tables, t-tests, ANOVAs and regression. Bayesian statistics are covered at the end of the book. For more information (and the opportunity to check the book out before you buy!) visit http://ua.edu.au/ccs/teaching/lsr or http://learningstatisticswithr.com
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 28
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Book Description
Author: Jelke Bethlehem
Publisher: John Wiley & Sons
ISBN: 0470494980
Category : Mathematics
Languages : en
Pages : 394
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Book Description
A complete, hands-on guide to the use of statistical methods for obtaining reliable and practical survey research Applied Survey Methods provides a comprehensive outline of the complete survey process, from design to publication. Filling a gap in the current literature, this one-of-a-kind book describes both the theory and practical applications of survey research with an emphasis on the statistical aspects of survey methods. The book begins with a brief historic overview of survey research methods followed by a discussion that details the needed first steps for carrying out a survey, including the definition of a target population, the selection of a sampling frame, and the outline of a questionnaire with several examples that include common errors to avoid in the wording of questions. Throughout the book, the author provides an accessible discussion on the methodological problems that are associated with the survey process, outlining real data and examples while also providing insight on the future of survey research. Chapter coverage explores the various aspects of the survey process and the accompanying numerical techniques, including: Simple and composite sampling designs Estimators Data collection and editing The quality of results The non-response problem Weighting adjustments and methods Disclosure control The final chapter addresses the growing popularity of Web surveys, and the associated methodological problems are discussed, including solutions to common pitfalls. Exercises are provided throughout with selected answers included at the end of the book, while a related Web site features additional solutions to exercises and a downloadable demo version of the Blaise system of computer-assisted interviewing. Access to the freely available SimSam software is also available on the related Web site and provides readers with the tools needed to simulate samples from finite populations as well as visualize the effects of sample size, non-response, and the use of different estimation procedures. Applied Survey Methods is an excellent book for courses on survey research and non-response in surveys at the upper-undergraduate and graduate levels. It is also a useful reference for practicing statisticians and survey methodologists who work in both government and private research sectors.
