Computer Intensive Statistical Methods
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Computer Intensive Statistical Methods
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Author : J. S. Urban. Hjorth
language : en
Publisher: CRC Press
Release Date : 1993-11-01
Computer Intensive Statistical Methods written by J. S. Urban. Hjorth and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1993-11-01 with Mathematics categories.
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.
Computer Intensive Methods In Statistics
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Author : Silvelyn Zwanzig
language : en
Publisher: CRC Press
Release Date : 2019-12-11
Computer Intensive Methods In Statistics written by Silvelyn Zwanzig and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-11 with Business & Economics categories.
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.
Computer Intensive Statistical Methods
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Author : J. S. Urban. Hjorth
language : en
Publisher: Routledge
Release Date : 2017-10-19
Computer Intensive Statistical Methods written by J. S. Urban. Hjorth and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-10-19 with Mathematics categories.
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.
Computer Intensive Statistical Methods
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Author : Stanford University. Division of Biostatistics
language : en
Publisher:
Release Date : 1995
Computer Intensive Statistical Methods written by Stanford University. Division of Biostatistics and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995 with categories.
Statistical Methods In Water Resources
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Author : D.R. Helsel
language : en
Publisher: Elsevier
Release Date : 1993-03-03
Statistical Methods In Water Resources written by D.R. Helsel and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 1993-03-03 with Science categories.
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.
An Introduction To Statistical Computing
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Author : Jochen Voss
language : en
Publisher: John Wiley & Sons
Release Date : 2013-10-28
An Introduction To Statistical Computing written by Jochen Voss and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-10-28 with Mathematics categories.
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
Elements Of Statistical Computing
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Author : R.A. Thisted
language : en
Publisher: Routledge
Release Date : 2017-10-19
Elements Of Statistical Computing written by R.A. Thisted and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-10-19 with Mathematics categories.
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.
Computer Intensive Statistical Methods
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Author : J. S. Urban Hjorth
language : en
Publisher:
Release Date : 1999
Computer Intensive Statistical Methods written by J. S. Urban Hjorth and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with MATHEMATICS categories.
"In engineering work and other practical situations, methods of a ""non-stop"" character are often needed. The computer intensive methods outlined in this book should show how to pass many obstacles that could not previously be overcome. Much emphasis in this book is placed on applications in science, economics, reliability, meteorology, medicine and transportation. In principle every area where data deserve statistical analyses there is a relevant application of these new methods. This book is aimed at classically educated statisticians as well as the younger generation. The key points of the book include: an introduction to the ""bootstrap"" method at elementary and advanced levels, examples of computer programmes and a review of the new methodology and its applications."--Provided by publisher.
Mathematica Laboratories For Mathematical Statistics
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Author : Jenny A. Baglivo
language : en
Publisher: SIAM
Release Date : 2005-01-01
Mathematica Laboratories For Mathematical Statistics written by Jenny A. Baglivo and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-01-01 with Mathematics categories.
Integrating computers into mathematical statistics courses allows students to simulate experiments and visualize their results, handle larger data sets, analyze data more quickly, and compare the results of classical methods of data analysis with those using alternative techniques. This text presents a concise introduction to the concepts of probability theory and mathematical statistics. The accompanying in-class and take-home computer laboratory activities reinforce the techniques introduced in the text and are accessible to students with little or no experience with Mathematica. These laboratory materials present applications in a variety of real-world settings, with data from epidemiology, environmental sciences, medicine, social sciences, physical sciences, manufacturing, engineering, marketing, and sports. Mathematica Laboratories for Mathematical Statistics: Emphasizing Simulation and Computer Intensive Methods includes parametric, nonparametric, permutation, bootstrap and diagnostic methods. Chapters on permutation and bootstrap techniques follow the formal inference chapters and precede the chapters on intermediate-level topics. Permutation and bootstrap methods are discussed side by side with classical methods in the later chapters.
Computational Statistics
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Author : James E. Gentle
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-07-28
Computational Statistics written by James E. Gentle and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-07-28 with Mathematics categories.
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.