Elements of Computational Statistics

Will provide a more elementary introduction to these topics than other books available; Gentle is the author of two other Springer books This book describes techniques used in computational statistics and considers some of the areas of ...

DOWNLOAD NOW »

Author: James E. Gentle

Publisher: Springer Science & Business Media

ISBN: 9780387216119

Category: Computers

Page: 420

View: 739

Will provide a more elementary introduction to these topics than other books available; Gentle is the author of two other Springer books

Basic Elements of Computational Statistics

QuantNet and the corresponding Data-Driven Documents-based visualization allows readers to reproduce the tables, pictures and calculations inside this Springer book.

DOWNLOAD NOW »

Author: Wolfgang Karl Härdle

Publisher: Springer

ISBN: 9783319553368

Category: Computers

Page: 305

View: 493

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.

Elements of Statistical Computing

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.

DOWNLOAD NOW »

Author: R.A. Thisted

Publisher: Routledge

ISBN: 9781351452755

Category: Mathematics

Page: 448

View: 980

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.

Computational Statistics

In addition, the handy appendix includes a collection of R language elements and functions, serving as a quick reference and starting point to access the rich information that comes bundled with R. Accessible to a broad audience, this book ...

DOWNLOAD NOW »

Author: Günther Sawitzki

Publisher: CRC Press

ISBN: 9781420086812

Category: Mathematics

Page: 264

View: 134

Suitable for a compact course or self-study, Computational Statistics: An Introduction to R illustrates how to use the freely available R software package for data analysis, statistical programming, and graphics. Integrating R code and examples throughout, the text only requires basic knowledge of statistics and computing. This introduction covers one-sample analysis and distribution diagnostics, regression, two-sample problems and comparison of distributions, and multivariate analysis. It uses a range of examples to demonstrate how R can be employed to tackle statistical problems. In addition, the handy appendix includes a collection of R language elements and functions, serving as a quick reference and starting point to access the rich information that comes bundled with R. Accessible to a broad audience, this book explores key topics in data analysis, regression, statistical distributions, and multivariate statistics. Full of examples and with a color insert, it helps readers become familiar with R.

The Grammar of Graphics

The first edition has sold more than 2200 copies. Four color throughout. This book was written for statisticians, computer scientists, geographers, researchers, and others interested in visualizing data.

DOWNLOAD NOW »

Author: Leland Wilkinson

Publisher: Springer Science & Business Media

ISBN: 0387245448

Category: Computers

Page: 691

View: 335

Presents a unique foundation for producing almost every quantitative graphic found in scientific journals, newspapers, statistical packages, and data visualization systems The new edition features six new chapters and has undergone substantial revision. The first edition has sold more than 2200 copies. Four color throughout.

Computational Statistics Data Analysis

Define the vector e = e ( 0 ) to have ith element ( y ; nT ; ) / Vn ; this vector is Op ( 1
) , where P denotes probability . Let F be the m x p derivative matrix of rank p with
elements Ôn ; / 20 , ( i = 1 , ... , m ; r = 1 , ... , p ) , and let F. be the px p matrix ...

DOWNLOAD NOW »

Author:

Publisher:

ISBN: OSU:32435069063733

Category: Mathematical statistics

Page:

View: 477

Technometrics

The maximum of ( A . 4 ) as a function of 8 occurs when both elements of the
minimum coincide , and this gives ( 12 ) . ... for Robust Principal Components
Based on Projection Pursuit , ” in Compstat : Proceedings in Computational
Statistics ...

DOWNLOAD NOW »

Author:

Publisher:

ISBN: UOM:39015065057591

Category: Experimental design

Page:

View: 337

Introduction to Statistics

This book covers all the topics found in introductory descriptive statistics courses, including simple linear regression and time series analysis, the fundamentals of inferential statistics (probability theory, random sampling and ...

DOWNLOAD NOW »

Author: Wolfgang Karl Härdle

Publisher: Springer

ISBN: 9783319177045

Category: Business & Economics

Page: 516

View: 970

This book covers all the topics found in introductory descriptive statistics courses, including simple linear regression and time series analysis, the fundamentals of inferential statistics (probability theory, random sampling and estimation theory), and inferential statistics itself (confidence intervals, testing). Each chapter starts with the necessary theoretical background, which is followed by a variety of examples. The core examples are based on the content of the respective chapter, while the advanced examples, designed to deepen students’ knowledge, also draw on information and material from previous chapters. The enhanced online version helps students grasp the complexity and the practical relevance of statistical analysis through interactive examples and is suitable for undergraduate and graduate students taking their first statistics courses, as well as for undergraduate students in non-mathematical fields, e.g. economics, the social sciences etc.

Computational Statistics

DOWNLOAD NOW »

Author: Peter Dirschedl

Publisher: Physica

ISBN: UOM:39015053931344

Category: Business & Economics

Page: 552

View: 510

This book is a collection of thirty invited papers, covering the important parts of a rapidly developing area like "computational statistics". All contributions supply information about a specialized topic in a tutorial and comprehensive style. Newest results and developments are discussed. Starting with the foundations of computational statistics, i.e. numerical reliability of software packages or construction principles for pseudorandom number generators, the volume includes design considerations on statistical programming languages and the basic issues of resampling techniques. Also covered are areas like design of experiments, graphical techniques, modelling and testing problems, a review of clustering algorithms, and concise discussions of regression trees or cognitive aspects of authoring systems.

Statistical Computing

Emphasizing the most accurate and widely used of these methods, the book thoroughly describes the algorithms that have been incorporated into the leading software systems of today, and discusses techniques for implementing algorithms in a ...

DOWNLOAD NOW »

Author: Kennedy

Publisher: CRC Press

ISBN: 0824768981

Category: Mathematics

Page: 608

View: 512

In this convenient textbook and reference work, the reader will find an introduction to statistical computing and a critical, balanced presentation of the algorithms and computational methods currently in use. Emphasizing the most accurate and widely used of these methods, the book thoroughly describes the algorithms that have been incorporated into the leading software systems of today, and discusses techniques for implementing algorithms in a computer. Statistical Computing contains the detail that researchers need, in the form of a textbook that gives advanced students a broad understanding of the subject, even in its most sophisticated aspects. Complete with exercises and extensive reference lists, Statistical Computing can be applied to a one-semester course for graduate students in statistics, mathematics, computer science, and any field in which numerical methods and algorithms are used in statistical data analyses. Book jacket.

Journal of the American Statistical Association

REFERENCES the elements of a sum to one , it is straightforward to show that
Kui ce , hCxhan = 1 , and hence à = ( à 1 ... Categorical Data With Covariates and
Missing Entries , " Computational Statistics & Data Analysis , 51 , 5236 – 5246 .

DOWNLOAD NOW »

Author:

Publisher:

ISBN: UCLA:L0098924103

Category: Statistics

Page:

View: 260

Journal of the Japanese Society of Computational Statistics

In this problem , we treat the joint density function ( 3 ) only since we fail to obtain
the suitable integration - by - parts formula under the joint density ( 2 ) to get
improved estimators . We first obtain the best estimator among the constant
multiple ...

DOWNLOAD NOW »

Author:

Publisher:

ISBN: UOM:39015072619904

Category: Mathematical statistics

Page:

View: 377

Numerical Linear Algebra for Applications in Statistics

Numerous exercises allow the text to be used for a first course in statistical computing or as supplementary text for various courses that emphasise computations.

DOWNLOAD NOW »

Author: James E. Gentle

Publisher: Springer Science & Business Media

ISBN: 0387985425

Category: Mathematics

Page: 221

View: 380

Accurate and efficient computer algorithms for factoring matrices, solving linear systems of equations, and extracting eigenvalues and eigenvectors. Regardless of the software system used, the book describes and gives examples of the use of modern computer software for numerical linear algebra. It begins with a discussion of the basics of numerical computations, and then describes the relevant properties of matrix inverses, factorisations, matrix and vector norms, and other topics in linear algebra. The book is essentially self- contained, with the topics addressed constituting the essential material for an introductory course in statistical computing. Numerous exercises allow the text to be used for a first course in statistical computing or as supplementary text for various courses that emphasise computations.

Introduction to Robust Estimation and Hypothesis Testing

Computational Statistics and Data Analysis, 20, 185–202. Schwertman ...
Principal components analysis for data containing outliers and missing elements.
... Communications in Statistics – Simulation and Computation, 37, 337–345.
Shao, J.

DOWNLOAD NOW »

Author: Rand R. Wilcox

Publisher: Academic Press

ISBN: 9780128047811

Category: Mathematics

Page: 810

View: 816

Introduction to Robust Estimating and Hypothesis Testing, 4th Editon, is a ‘how-to’ on the application of robust methods using available software. Modern robust methods provide improved techniques for dealing with outliers, skewed distribution curvature and heteroscedasticity that can provide substantial gains in power as well as a deeper, more accurate and more nuanced understanding of data. Since the last edition, there have been numerous advances and improvements. They include new techniques for comparing groups and measuring effect size as well as new methods for comparing quantiles. Many new regression methods have been added that include both parametric and nonparametric techniques. The methods related to ANCOVA have been expanded considerably. New perspectives related to discrete distributions with a relatively small sample space are described as well as new results relevant to the shift function. The practical importance of these methods is illustrated using data from real world studies. The R package written for this book now contains over 1200 functions. New to this edition 35% revised content Covers many new and improved R functions New techniques that deal with a wide range of situations Extensive revisions to cover the latest developments in robust regression Covers latest improvements in ANOVA Includes newest rank-based methods Describes and illustrated easy to use software

Applied Computational Statistics in Longitudinal Research

UNIVARIATE SUMMARY STATISTICS SAMPLE SIZE STANDARD DEVIATION
COEFFICIENT OF VARIATION SMALLEST ... PAIRWISE PERCENTAGES OF
MISSING DATA DIAGONAL ELEMENTS ARE THE PERCENTAGES THAT EACH
 ...

DOWNLOAD NOW »

Author: Michael J. Rovine

Publisher:

ISBN: UOM:39015024788369

Category: Medicine

Page: 237

View: 571

New sophisticated data analytic strategies have become available to longitudinal researchers, but while information regarding the theory of these methods is available, that theory often does not help the user implement the strategy. Applied Computational Statistics in Longitudinal Research is designed to assist the user to actually run and interpret the results of many of these analytic strategies. Each chapter in the book deals with a different technique and the discussion begins with a summary of the procedure. An example including both the setup of the program and an annotated output are carefully explained. Unlike many other books on these topics, this book helps the user to quickly and easily apply the material to the computer. It can either be used as a companion to the two-volume Statistical Methods in Longitudinal Research (edited by von Eye, Academic Press, September, 1990) or alone to illustrate the applications of statistical methods that can be used in psychology, sociology, medicine, education, and engineering.

Proceedings of the Section on Statistical Education

Graduate Education in Computational Statistics * * WILLIAM F . EDDY , ALBYN C
. JONES , ROBERT E . KASS , and MARK J ... Some of these techniques have
now become standard components of statistical analysis packages .

DOWNLOAD NOW »

Author: American Statistical Association. Section on Statistical Education

Publisher:

ISBN: UOM:39015027080798

Category: Educational statistics

Page:

View: 280

Proceedings of COMPSTAT 2010

19th International Conference on Computational StatisticsParis France, August
22-27, 2010 Keynote, Invited and Contributed ... This becomes even more
important when the data also contain missing elements and the DetMCD
algorithm is ...

DOWNLOAD NOW »

Author: Yves Lechevallier

Publisher: Springer Science & Business Media

ISBN: 9783790826043

Category: Computers

Page: 621

View: 469

Proceedings of the 19th international symposium on computational statistics, held in Paris august 22-27, 2010.Together with 3 keynote talks, there were 14 invited sessions and more than 100 peer-reviewed contributed communications.

Data Warehousing and Mining

Elements of computational statistics . New York : Springer - Verlag . Muller , K . -
R . , Mika , S . , Ratsch , G . , Tsuda , K . , & Scholkopf , B . ( 2001 ) . An
introduction to kernelbased learning algorithms . IEEE Transactions on Neural
Networks ...

DOWNLOAD NOW »

Author: John Wang

Publisher:

ISBN: 1599049511

Category: Data mining

Page: 3719

View: 992

"This collection offers tools, designs, and outcomes of the utilization of data mining and warehousing technologies, such as algorithms, concept lattices, multidimensional data, and online analytical processing. With more than 300 chapters contributed by over 575 experts from around the globe, this authoritative collection will provide libraries with the essential reference on data mining and warehousing"--Provided by publisher.

Matrix Algebra

Matrix algebra is one of the most important areas of mathematics for data analysis and for statistical theory. This much-needed work presents the relevant aspects of the theory of matrix algebra for applications in statistics.

DOWNLOAD NOW »

Author: James E. Gentle

Publisher: Springer Science & Business Media

ISBN: 9780387708720

Category: Computers

Page: 528

View: 604

This much-needed work presents, among other things, the relevant aspects of the theory of matrix algebra for applications in statistics. Written in an informal style, it addresses computational issues and places more emphasis on applications than existing texts.

Journal of Computational and Graphical Statistics

A Joint Publication of American Statistical Association, Institute of Mathematical
Statistics, Interface Foundation of North America ... Thisted , R. A. ( 1988 ) ,
Elements of Statistical Computing , New York : Chapman and Hall . Upensky ,
J. V. ...

DOWNLOAD NOW »

Author:

Publisher:

ISBN: UCSD:31822033898875

Category: Mathematical statistics

Page:

View: 348