Basic Elements Of Computational Statistics PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Basic Elements Of Computational Statistics PDF full book. Access full book title Basic Elements Of Computational Statistics.
Author | : James E. Gentle |
Publisher | : Springer Science & Business Media |
Total Pages | : 427 |
Release | : 2006-04-18 |
Genre | : Computers |
ISBN | : 0387216111 |
Download Elements of Computational Statistics Book in PDF, ePub and Kindle
Will provide a more elementary introduction to these topics than other books available; Gentle is the author of two other Springer books
Author | : Wolfgang Karl Härdle |
Publisher | : Springer |
Total Pages | : 318 |
Release | : 2017-09-29 |
Genre | : Computers |
ISBN | : 3319553364 |
Download Basic Elements of Computational Statistics Book in PDF, ePub and Kindle
This textbook on computational statistics presents tools and concepts of univariate and multivariate statistical data analysis with a strong focus on applications and implementations in the statistical software R. It covers mathematical, statistical as well as programming problems in computational statistics and contains a wide variety of practical examples. In addition to the numerous R sniplets presented in the text, all computer programs (quantlets) and data sets to the book are available on GitHub and referred to in the book. This enables the reader to fully reproduce as well as modify and adjust all examples to their needs. The book is intended for advanced undergraduate and first-year graduate students as well as for data analysts new to the job who would like a tour of the various statistical tools in a data analysis workshop. The experienced reader with a good knowledge of statistics and programming might skip some sections on univariate models and enjoy the various ma thematical roots of multivariate techniques. The Quantlet platform quantlet.de, quantlet.com, quantlet.org is an integrated QuantNet environment consisting of different types of statistics-related documents and program codes. Its goal is to promote reproducibility and offer a platform for sharing validated knowledge native to the social web. QuantNet and the corresponding Data-Driven Documents-based visualization allows readers to reproduce the tables, pictures and calculations inside this Springer book.
Author | : R.A. Thisted |
Publisher | : Routledge |
Total Pages | : 448 |
Release | : 2017-10-19 |
Genre | : Mathematics |
ISBN | : 1351452754 |
Download Elements of Statistical Computing Book in PDF, ePub and Kindle
Statistics and computing share many close relationships. Computing now permeates every aspect of statistics, from pure description to the development of statistical theory. At the same time, the computational methods used in statistical work span much of computer science. Elements of Statistical Computing covers the broad usage of computing in statistics. It provides a comprehensive account of the most important computational statistics. Included are discussions of numerical analysis, numerical integration, and smoothing. The author give special attention to floating point standards and numerical analysis; iterative methods for both linear and nonlinear equation, such as Gauss-Seidel method and successive over-relaxation; and computational methods for missing data, such as the EM algorithm. Also covered are new areas of interest, such as the Kalman filter, projection-pursuit methods, density estimation, and other computer-intensive techniques.
Author | : Springer |
Publisher | : |
Total Pages | : 444 |
Release | : 2014-01-15 |
Genre | : |
ISBN | : 9781475777017 |
Download Elements of Computational Statistics Book in PDF, ePub and Kindle
Author | : James E. Gentle |
Publisher | : Springer Science & Business Media |
Total Pages | : 1180 |
Release | : 2012-07-06 |
Genre | : Computers |
ISBN | : 3642215513 |
Download Handbook of Computational Statistics Book in PDF, ePub and Kindle
The Handbook of Computational Statistics - Concepts and Methods (second edition) is a revision of the first edition published in 2004, and contains additional comments and updated information on the existing chapters, as well as three new chapters addressing recent work in the field of computational statistics. This new edition is divided into 4 parts in the same way as the first edition. It begins with "How Computational Statistics became the backbone of modern data science" (Ch.1): an overview of the field of Computational Statistics, how it emerged as a separate discipline, and how its own development mirrored that of hardware and software, including a discussion of current active research. The second part (Chs. 2 - 15) presents several topics in the supporting field of statistical computing. Emphasis is placed on the need for fast and accurate numerical algorithms, and some of the basic methodologies for transformation, database handling, high-dimensional data and graphics treatment are discussed. The third part (Chs. 16 - 33) focuses on statistical methodology. Special attention is given to smoothing, iterative procedures, simulation and visualization of multivariate data. Lastly, a set of selected applications (Chs. 34 - 38) like Bioinformatics, Medical Imaging, Finance, Econometrics and Network Intrusion Detection highlight the usefulness of computational statistics in real-world applications.
Author | : James E. Gentle |
Publisher | : Springer Science & Business Media |
Total Pages | : 732 |
Release | : 2009-07-28 |
Genre | : Mathematics |
ISBN | : 0387981446 |
Download Computational Statistics Book in PDF, ePub and Kindle
Computational inference is based on an approach to statistical methods that uses modern computational power to simulate distributional properties of estimators and test statistics. This book describes computationally intensive statistical methods in a unified presentation, emphasizing techniques, such as the PDF decomposition, that arise in a wide range of methods.
Author | : |
Publisher | : Springer Science & Business Media |
Total Pages | : 732 |
Release | : 2010-04-29 |
Genre | : Mathematics |
ISBN | : 0387981454 |
Download Computational Statistics Book in PDF, ePub and Kindle
Computational inference is based on an approach to statistical methods that uses modern computational power to simulate distributional properties of estimators and test statistics. This book describes computationally intensive statistical methods in a unified presentation, emphasizing techniques, such as the PDF decomposition, that arise in a wide range of methods.
Author | : Geof H. Givens |
Publisher | : John Wiley & Sons |
Total Pages | : 496 |
Release | : 2012-10-09 |
Genre | : Mathematics |
ISBN | : 1118555481 |
Download Computational Statistics Book in PDF, ePub and Kindle
This new edition continues to serve as a comprehensive guide to modern and classical methods of statistical computing. The book is comprised of four main parts spanning the field: Optimization Integration and Simulation Bootstrapping Density Estimation and Smoothing Within these sections,each chapter includes a comprehensive introduction and step-by-step implementation summaries to accompany the explanations of key methods. The new edition includes updated coverage and existing topics as well as new topics such as adaptive MCMC and bootstrapping for correlated data. The book website now includes comprehensive R code for the entire book. There are extensive exercises, real examples, and helpful insights about how to use the methods in practice.
Author | : Jochen Voss |
Publisher | : John Wiley & Sons |
Total Pages | : 322 |
Release | : 2013-08-28 |
Genre | : Mathematics |
ISBN | : 1118728025 |
Download An Introduction to Statistical Computing Book in PDF, ePub and Kindle
A comprehensive introduction to sampling-based methods in statistical computing The use of computers in mathematics and statistics has opened up a wide range of techniques for studying otherwise intractable problems. Sampling-based simulation techniques are now an invaluable tool for exploring statistical models. This book gives a comprehensive introduction to the exciting area of sampling-based methods. An Introduction to Statistical Computing introduces the classical topics of random number generation and Monte Carlo methods. It also includes some advanced methods such as the reversible jump Markov chain Monte Carlo algorithm and modern methods such as approximate Bayesian computation and multilevel Monte Carlo techniques An Introduction to Statistical Computing: Fully covers the traditional topics of statistical computing. Discusses both practical aspects and the theoretical background. Includes a chapter about continuous-time models. Illustrates all methods using examples and exercises. Provides answers to the exercises (using the statistical computing environment R); the corresponding source code is available online. Includes an introduction to programming in R. This book is mostly self-contained; the only prerequisites are basic knowledge of probability up to the law of large numbers. Careful presentation and examples make this book accessible to a wide range of students and suitable for self-study or as the basis of a taught course.
Author | : Ronald Aaron Thisted |
Publisher | : |
Total Pages | : |
Release | : 1988 |
Genre | : Electronic book |
ISBN | : |
Download Elements of Statistical Computing Book in PDF, ePub and Kindle