Multivariate Statistical Simulation
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Multivariate Statistical Simulation
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Author : Mark E. Johnson
language : en
Publisher: John Wiley & Sons
Release Date : 1987-02-04
Multivariate Statistical Simulation written by Mark E. Johnson 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 1987-02-04 with Mathematics categories.
Provides state-of-the-art coverage for the researcher confronted with designing and executing a simulation study using continuous multivariate distributions. Concise writing style makes the book accessible to a wide audience. Well-known multivariate distributions are described, emphasizing a few representative cases from each distribution. Coverage includes Pearson Types II and VII elliptically contoured distributions, Khintchine distributions, and the unifying class for the Burr, Pareto, and logistic distributions. Extensively illustrated--the figures are unique, attractive, and reveal very nicely what distributions ``look like.'' Contains an extensive and up-to-date bibliography culled from journals in statistics, operations research, mathematics, and computer science.
Multivariate Statistical Simulation
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Author : Mark e.. Johnson
language : en
Publisher:
Release Date : 1992
Multivariate Statistical Simulation written by Mark e.. Johnson and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992 with categories.
Handbook Of Applied Multivariate Statistics And Mathematical Modeling
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Author : Howard E.A. Tinsley
language : en
Publisher: Academic Press
Release Date : 2000-05-22
Handbook Of Applied Multivariate Statistics And Mathematical Modeling written by Howard E.A. Tinsley and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000-05-22 with Mathematics categories.
Multivariate statistics and mathematical models provide flexible and powerful tools essential in most disciplines. Nevertheless, many practicing researchers lack an adequate knowledge of these techniques, or did once know the techniques, but have not been able to keep abreast of new developments. The Handbook of Applied Multivariate Statistics and Mathematical Modeling explains the appropriate uses of multivariate procedures and mathematical modeling techniques, and prescribe practices that enable applied researchers to use these procedures effectively without needing to concern themselves with the mathematical basis. The Handbook emphasizes using models and statistics as tools. The objective of the book is to inform readers about which tool to use to accomplish which task. Each chapter begins with a discussion of what kinds of questions a particular technique can and cannot answer. As multivariate statistics and modeling techniques are useful across disciplines, these examples include issues of concern in biological and social sciences as well as the humanities.
Essentials Of Monte Carlo Simulation
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Author : Nick T. Thomopoulos
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-19
Essentials Of Monte Carlo Simulation written by Nick T. Thomopoulos 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 2012-12-19 with Mathematics categories.
Essentials of Monte Carlo Simulation focuses on the fundamentals of Monte Carlo methods using basic computer simulation techniques. The theories presented in this text deal with systems that are too complex to solve analytically. As a result, readers are given a system of interest and constructs using computer code, as well as algorithmic models to emulate how the system works internally. After the models are run several times, in a random sample way, the data for each output variable(s) of interest is analyzed by ordinary statistical methods. This book features 11 comprehensive chapters, and discusses such key topics as random number generators, multivariate random variates, and continuous random variates. Over 100 numerical examples are presented as part of the appendix to illustrate useful real world applications. The text also contains an easy to read presentation with minimal use of difficult mathematical concepts. Very little has been published in the area of computer Monte Carlo simulation methods, and this book will appeal to students and researchers in the fields of Mathematics and Statistics.
Monte Carlo Simulation Based Statistical Modeling
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Author : Ding-Geng (Din) Chen
language : en
Publisher: Springer
Release Date : 2017-02-01
Monte Carlo Simulation Based Statistical Modeling written by Ding-Geng (Din) Chen and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-02-01 with Medical categories.
This book brings together expert researchers engaged in Monte-Carlo simulation-based statistical modeling, offering them a forum to present and discuss recent issues in methodological development as well as public health applications. It is divided into three parts, with the first providing an overview of Monte-Carlo techniques, the second focusing on missing data Monte-Carlo methods, and the third addressing Bayesian and general statistical modeling using Monte-Carlo simulations. The data and computer programs used here will also be made publicly available, allowing readers to replicate the model development and data analysis presented in each chapter, and to readily apply them in their own research. Featuring highly topical content, the book has the potential to impact model development and data analyses across a wide spectrum of fields, and to spark further research in this direction.
Simulating Data With Sas
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Author : Rick Wicklin
language : en
Publisher: SAS Institute
Release Date : 2013-04-22
Simulating Data With Sas written by Rick Wicklin and has been published by SAS Institute this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-04-22 with Computers categories.
Data simulation is a fundamental technique in statistical programming and research. Rick Wicklin's Simulating Data with SAS brings together the most useful algorithms and the best programming techniques for efficient data simulation in an accessible how-to book for practicing statisticians and statistical programmers. This book discusses in detail how to simulate data from common univariate and multivariate distributions, and how to use simulation to evaluate statistical techniques. It also covers simulating correlated data, data for regression models, spatial data, and data with given moments. It provides tips and techniques for beginning programmers, and offers libraries of functions for advanced practitioners. As the first book devoted to simulating data across a range of statistical applications, Simulating Data with SAS is an essential tool for programmers, analysts, researchers, and students who use SAS software. This book is part of the SAS Press program.
Multivariate Statistical Process Control With Industrial Applications
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Author : Robert L. Mason
language : en
Publisher: SIAM
Release Date : 2002-01-01
Multivariate Statistical Process Control With Industrial Applications written by Robert L. Mason and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002-01-01 with Technology & Engineering categories.
Detailed coverage of the practical aspects of multivariate statistical process control (MVSPC) based on the application of Hotelling's T2 statistic. MVSPC is the application of multivariate statistical techniques to improve the quality and productivity of an industrial process. Provides valuable insight into the T2 statistic.
Graphical Models In Applied Multivariate Statistics
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Author : Joe Whittaker
language : en
Publisher: Wiley
Release Date : 2009-03-02
Graphical Models In Applied Multivariate Statistics written by Joe Whittaker and has been published by Wiley this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-03-02 with Mathematics categories.
The Wiley Paperback Series makes valuable content more accessible to a new generation of statisticians, mathematicians and scientists. Graphical models--a subset of log-linear models--reveal the interrelationships between multiple variables and features of the underlying conditional independence. This introduction to the use of graphical models in the description and modeling of multivariate systems covers conditional independence, several types of independence graphs, Gaussian models, issues in model selection, regression and decomposition. Many numerical examples and exercises with solutions are included. This book is aimed at students who require a course on applied multivariate statistics unified by the concept of conditional independence and researchers concerned with applying graphical modelling techniques.
Multivariate Data Analysis
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Author : Kim H. Esbensen
language : en
Publisher:
Release Date : 2018
Multivariate Data Analysis written by Kim H. Esbensen and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with Multivariate analysis categories.
Linear Time Series With Matlab And Octave
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Author : Víctor Gómez
language : en
Publisher: Springer Nature
Release Date : 2019-10-04
Linear Time Series With Matlab And Octave written by Víctor Gómez and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-04 with Computers categories.
This book presents an introduction to linear univariate and multivariate time series analysis, providing brief theoretical insights into each topic, and from the beginning illustrating the theory with software examples. As such, it quickly introduces readers to the peculiarities of each subject from both theoretical and the practical points of view. It also includes numerous examples and real-world applications that demonstrate how to handle different types of time series data. The associated software package, SSMMATLAB, is written in MATLAB and also runs on the free OCTAVE platform. The book focuses on linear time series models using a state space approach, with the Kalman filter and smoother as the main tools for model estimation, prediction and signal extraction. A chapter on state space models describes these tools and provides examples of their use with general state space models. Other topics discussed in the book include ARIMA; and transfer function and structural models; as well as signal extraction using the canonical decomposition in the univariate case, and VAR, VARMA, cointegrated VARMA, VARX, VARMAX, and multivariate structural models in the multivariate case. It also addresses spectral analysis, the use of fixed filters in a model-based approach, and automatic model identification procedures for ARIMA and transfer function models in the presence of outliers, interventions, complex seasonal patterns and other effects like Easter, trading day, etc. This book is intended for both students and researchers in various fields dealing with time series. The software provides numerous automatic procedures to handle common practical situations, but at the same time, readers with programming skills can write their own programs to deal with specific problems. Although the theoretical introduction to each topic is kept to a minimum, readers can consult the companion book ‘Multivariate Time Series With Linear State Space Structure’, by the same author, if they require more details.