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Author: J. S. Urban. Hjorth
Publisher: Routledge
ISBN: 1351458744
Category : Mathematics
Languages : en
Pages : 280
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Book Description
This book focuses on computer intensive statistical methods, such as validation, model selection, and bootstrap, that help overcome obstacles that could not be previously solved by methods such as regression and time series modelling in the areas of economics, meteorology, and transportation.
Author: J. S. Urban. Hjorth
Publisher: Routledge
ISBN: 1351458744
Category : Mathematics
Languages : en
Pages : 280
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Book Description
This book focuses on computer intensive statistical methods, such as validation, model selection, and bootstrap, that help overcome obstacles that could not be previously solved by methods such as regression and time series modelling in the areas of economics, meteorology, and transportation.
Author: Silvelyn Zwanzig
Publisher: CRC Press
ISBN: 0429510942
Category : Business & Economics
Languages : en
Pages : 227
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Book Description
This textbook gives an overview of statistical methods that have been developed during the last years due to increasing computer use, including random number generators, Monte Carlo methods, Markov Chain Monte Carlo (MCMC) methods, Bootstrap, EM algorithms, SIMEX, variable selection, density estimators, kernel estimators, orthogonal and local polynomial estimators, wavelet estimators, splines, and model assessment. Computer Intensive Methods in Statistics is written for students at graduate level, but can also be used by practitioners. Features Presents the main ideas of computer-intensive statistical methods Gives the algorithms for all the methods Uses various plots and illustrations for explaining the main ideas Features the theoretical backgrounds of the main methods. Includes R codes for the methods and examples Silvelyn Zwanzig is an Associate Professor for Mathematical Statistics at Uppsala University. She studied Mathematics at the Humboldt- University in Berlin. Before coming to Sweden, she was Assistant Professor at the University of Hamburg in Germany. She received her Ph.D. in Mathematics at the Academy of Sciences of the GDR. Since 1991, she has taught Statistics for undergraduate and graduate students. Her research interests have moved from theoretical statistics to computer intensive statistics. Behrang Mahjani is a postdoctoral fellow with a Ph.D. in Scientific Computing with a focus on Computational Statistics, from Uppsala University, Sweden. He joined the Seaver Autism Center for Research and Treatment at the Icahn School of Medicine at Mount Sinai, New York, in September 2017 and was formerly a postdoctoral fellow at the Karolinska Institutet, Stockholm, Sweden. His research is focused on solving large-scale problems through statistical and computational methods.
Author: D.R. Helsel
Publisher: Elsevier
ISBN: 0080875084
Category : Science
Languages : en
Pages : 539
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Book Description
Data on water quality and other environmental issues are being collected at an ever-increasing rate. In the past, however, the techniques used by scientists to interpret this data have not progressed as quickly. This is a book of modern statistical methods for analysis of practical problems in water quality and water resources.The last fifteen years have seen major advances in the fields of exploratory data analysis (EDA) and robust statistical methods. The 'real-life' characteristics of environmental data tend to drive analysis towards the use of these methods. These advances are presented in a practical and relevant format. Alternate methods are compared, highlighting the strengths and weaknesses of each as applied to environmental data. Techniques for trend analysis and dealing with water below the detection limit are topics covered, which are of great interest to consultants in water-quality and hydrology, scientists in state, provincial and federal water resources, and geological survey agencies.The practising water resources scientist will find the worked examples using actual field data from case studies of environmental problems, of real value. Exercises at the end of each chapter enable the mechanics of the methodological process to be fully understood, with data sets included on diskette for easy use. The result is a book that is both up-to-date and immediately relevant to ongoing work in the environmental and water sciences.
Author: Eric W. Noreen
Publisher: Wiley-Interscience
ISBN:
Category : Mathematics
Languages : en
Pages : 246
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Book Description
How to use computer-intensive methods to assess the significance of a statistic in an hypothesis test--for both statisticians and nonstatisticians alike. The significance of almost any test can be assessed using one of the methods presented here, for the techniques given are very general (e.g. virtually every nonparametric statistical test is a special case of one of the methods covered). Programs presented are brief, easy to read, require minimal programming, and can be run on most PC's. They also serve as templates adaptable to a wide range of applications. Includes numerous illustrations of how to apply computer-intensive methods.
Author: Derek A. Roff
Publisher: Cambridge University Press
ISBN: 0521608651
Category : Medical
Languages : en
Pages : 233
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Book Description
Publisher Description
Author: R.A. Thisted
Publisher: Routledge
ISBN: 1351452746
Category : Mathematics
Languages : en
Pages : 456
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Book Description
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: Jenny A. Baglivo
Publisher: SIAM
ISBN: 0898715660
Category : Mathematics
Languages : en
Pages : 273
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Book Description
CD-ROM contains text, data, computations, and graphics.
Author: Bryan F. J. Manly
Publisher: Chapman & Hall/CRC
ISBN: 9780367512873
Category :
Languages : en
Pages : 338
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Book Description
The fourth edition of the book illustrates a large number of statistical methods with an emphasis on biological applications. It provides comprehensive coverage of computer-intensive applications, with datasets available online.
Author: Jochen Voss
Publisher: John Wiley & Sons
ISBN: 1118728025
Category : Mathematics
Languages : en
Pages : 322
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Book Description
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: Maria L. Rizzo
Publisher: CRC Press
ISBN: 1420010719
Category : Reference
Languages : en
Pages : 412
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Book Description
Computational statistics and statistical computing are two areas that employ computational, graphical, and numerical approaches to solve statistical problems, making the versatile R language an ideal computing environment for these fields. One of the first books on these topics to feature R, Statistical Computing with R covers the traditiona
