Statistical Decomposition Analysis
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Statistical Decomposition Analysis
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Author : Henri Theil
language : en
Publisher:
Release Date : 1972
Statistical Decomposition Analysis written by Henri Theil and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1972 with Decomposition method categories.
USA. Textbook on statistical analysis and mathematical analysis techniques for decomposition analysis, with applications in the social sciences and in management development sciences - explores ways to assess the factors which determine decompositions, etc. Bibliography pp. 325 to 328 and graphs.
Statistical Decomposition Analysis
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Author : Henri Theil
language : en
Publisher: North-Holland
Release Date : 1972
Statistical Decomposition Analysis written by Henri Theil and has been published by North-Holland this book supported file pdf, txt, epub, kindle and other format this book has been release on 1972 with Business & Economics categories.
Information and dividedness: racial integration, industrial diversity and the combining of assets on balance sheets; Extensions to several decompositions; Multidimensional extension; Decompositions and their determining factors; Social mobility and social distance: a markov chain approach.
Analysis Of Time Series Structure
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Author : Nina Golyandina
language : en
Publisher: CRC Press
Release Date : 2001-01-23
Analysis Of Time Series Structure written by Nina Golyandina and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001-01-23 with Mathematics categories.
Over the last 15 years, singular spectrum analysis (SSA) has proven very successful. It has already become a standard tool in climatic and meteorological time series analysis and well known in nonlinear physics and signal processing. However, despite the promise it holds for time series applications in other disciplines, SSA is not widely known among statisticians and econometrists, and although the basic SSA algorithm looks simple, understanding what it does and where its pitfalls lay is by no means simple. Analysis of Time Series Structure: SSA and Related Techniques provides a careful, lucid description of its general theory and methodology. Part I introduces the basic concepts, and sets forth the main findings and results, then presents a detailed treatment of the methodology. After introducing the basic SSA algorithm, the authors explore forecasting and apply SSA ideas to change-point detection algorithms. Part II is devoted to the theory of SSA. Here the authors formulate and prove the statements of Part I. They address the singular value decomposition (SVD) of real matrices, time series of finite rank, and SVD of trajectory matrices. Based on the authors' original work and filled with applications illustrated with real data sets, this book offers an outstanding opportunity to obtain a working knowledge of why, when, and how SSA works. It builds a strong foundation for successfully using the technique in applications ranging from mathematics and nonlinear physics to economics, biology, oceanology, social science, engineering, financial econometrics, and market research.
Statistical Decomposition Procedures And Their Application To Residential Sales Price Data
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Author : Paul Bernard Slater
language : en
Publisher:
Release Date : 1972
Statistical Decomposition Procedures And Their Application To Residential Sales Price Data written by Paul Bernard Slater and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1972 with categories.
Singular Spectrum Analysis For Time Series
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Author : Nina Golyandina
language : en
Publisher: Springer Nature
Release Date : 2020-11-23
Singular Spectrum Analysis For Time Series written by Nina Golyandina and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-23 with Mathematics categories.
This book gives an overview of singular spectrum analysis (SSA). SSA is a technique of time series analysis and forecasting combining elements of classical time series analysis, multivariate statistics, multivariate geometry, dynamical systems and signal processing. SSA is multi-purpose and naturally combines both model-free and parametric techniques, which makes it a very special and attractive methodology for solving a wide range of problems arising in diverse areas. Rapidly increasing number of novel applications of SSA is a consequence of the new fundamental research on SSA and the recent progress in computing and software engineering which made it possible to use SSA for very complicated tasks that were unthinkable twenty years ago. In this book, the methodology of SSA is concisely but at the same time comprehensively explained by two prominent statisticians with huge experience in SSA. The book offers a valuable resource for a very wide readership, including professional statisticians, specialists in signal and image processing, as well as specialists in numerous applied disciplines interested in using statistical methods for time series analysis, forecasting, signal and image processing. The second edition of the book contains many updates and some new material including a thorough discussion on the place of SSA among other methods and new sections on multivariate and multidimensional extensions of SSA.
Decomposition Analysis Method In Linear And Nonlinear Differential Equations
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Author : Kansari Haldar
language : en
Publisher: CRC Press
Release Date : 2015-10-22
Decomposition Analysis Method In Linear And Nonlinear Differential Equations written by Kansari Haldar and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-10-22 with Mathematics categories.
A Powerful Methodology for Solving All Types of Differential EquationsDecomposition Analysis Method in Linear and Non-Linear Differential Equations explains how the Adomian decomposition method can solve differential equations for the series solutions of fundamental problems in physics, astrophysics, chemistry, biology, medicine, and other scientif
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.
Understanding Complex Datasets
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Author : David Skillicorn
language : en
Publisher: CRC Press
Release Date : 2007-05-17
Understanding Complex Datasets written by David Skillicorn and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-05-17 with Computers categories.
Making obscure knowledge about matrix decompositions widely available, Understanding Complex Datasets: Data Mining with Matrix Decompositions discusses the most common matrix decompositions and shows how they can be used to analyze large datasets in a broad range of application areas. Without having to understand every mathematical detail, the book
Data Driven Fault Detection And Reasoning For Industrial Monitoring
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Author : Jing Wang
language : en
Publisher: Springer Nature
Release Date : 2022-01-03
Data Driven Fault Detection And Reasoning For Industrial Monitoring written by Jing Wang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-03 with Technology & Engineering categories.
This open access book assesses the potential of data-driven methods in industrial process monitoring engineering. The process modeling, fault detection, classification, isolation, and reasoning are studied in detail. These methods can be used to improve the safety and reliability of industrial processes. Fault diagnosis, including fault detection and reasoning, has attracted engineers and scientists from various fields such as control, machinery, mathematics, and automation engineering. Combining the diagnosis algorithms and application cases, this book establishes a basic framework for this topic and implements various statistical analysis methods for process monitoring. This book is intended for senior undergraduate and graduate students who are interested in fault diagnosis technology, researchers investigating automation and industrial security, professional practitioners and engineers working on engineering modeling and data processing applications. This is an open access book.
Numerical Analysis For Statisticians
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Author : Kenneth Lange
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-06-15
Numerical Analysis For Statisticians written by Kenneth Lange 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 2010-06-15 with Business & Economics categories.
Numerical analysis is the study of computation and its accuracy, stability and often its implementation on a computer. This book focuses on the principles of numerical analysis and is intended to equip those readers who use statistics to craft their own software and to understand the advantages and disadvantages of different numerical methods.