Linear Data-smoothing and Prediction in Theory and Practice PDF Download
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Author: Ralph Beebe Blackman
Publisher:
ISBN:
Category : Digital filters
Languages : en
Pages : 208
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Book Description
Author: Ralph Beebe Blackman
Publisher:
ISBN:
Category : Digital filters
Languages : en
Pages : 208
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Book Description
Author: Clifford E. Swartz
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Author: Ralph Beebe Blackman
Publisher:
ISBN:
Category : Digital filters (Mathematics)
Languages : en
Pages :
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Book Description
Author: Ralph Beebe Blackman
Publisher:
ISBN:
Category : Digital filters (Mathematics)
Languages : en
Pages : 208
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Book Description
Author:
Publisher:
ISBN:
Category : Physical instruments
Languages : en
Pages : 64
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Book Description
Author: Maria Cristina Mariani
Publisher: John Wiley & Sons
ISBN: 1119674689
Category : Mathematics
Languages : en
Pages : 404
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Book Description
DATA SCIENCE IN THEORY AND PRACTICE EXPLORE THE FOUNDATIONS OF DATA SCIENCE WITH THIS INSIGHTFUL NEW RESOURCE Data Science in Theory and Practice delivers a comprehensive treatment of the mathematical and statistical models useful for analyzing data sets arising in various disciplines, like banking, finance, health care, bioinformatics, security, education, and social services. Written in five parts, the book examines some of the most commonly used and fundamental mathematical and statistical concepts that form the basis of data science. The authors go on to analyze various data transformation techniques useful for extracting information from raw data, long memory behavior, and predictive modeling. The book offers readers a multitude of topics all relevant to the analysis of complex data sets. Along with a robust exploration of the theory underpinning data science, it contains numerous applications to specific and practical problems. The book also provides examples of code algorithms in R and Python and provides pseudo-algorithms to port the code to any other language. Ideal for students and practitioners without a strong background in data science, readers will also learn from topics like: Analyses of foundational theoretical subjects, including the history of data science, matrix algebra and random vectors, and multivariate analysis A comprehensive examination of time series forecasting, including the different components of time series and transformations to achieve stationarity Introductions to both the R and Python programming languages, including basic data types and sample manipulations for both languages An exploration of algorithms, including how to write one and how to perform an asymptotic analysis A comprehensive discussion of several techniques for analyzing and predicting complex data sets Perfect for advanced undergraduate and graduate students in Data Science, Business Analytics, and Statistics programs, Data Science in Theory and Practice will also earn a place in the libraries of practicing data scientists, data and business analysts, and statisticians in the private sector, government, and academia.
Author: Mark Walker
Publisher: Routledge
ISBN: 1136466622
Category : History
Languages : en
Pages : 284
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Book Description
Does science work best in a democracy? Were 'Soviet' or 'Nazi' science fundamentally different from science in the USA? These questions have been passionately debated in the recent past. Particular developments in science took place under particular political regimes, but they may or may not have been directly determined by them. Science and Ideology brings together a number of comparative case studies to examine the relationship between science and the dominant ideology of a state. Cybernetics in the USA is compared to France and the Soviet Union. Postwar Allied science policy in occupied Germany is juxtaposed to that in Japan. The essays are narrowly focussed, yet cover a wide range of countries and ideologies. The collection provides a unique comparative history of scientific policies and practices in the 20th century.
Author: David A. Mindell
Publisher: JHU Press
ISBN: 0801877741
Category : Science
Languages : en
Pages : 456
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Book Description
Today, we associate the relationship between feedback, control, and computing with Norbert Wiener's 1948 formulation of cybernetics. But the theoretical and practical foundations for cybernetics, control engineering, and digital computing were laid earlier, between the two world wars. In Between Human and Machine: Feedback, Control, and Computing before Cybernetics, David A. Mindell shows how the modern sciences of systems emerged from disparate engineering cultures and their convergence during World War II. Mindell examines four different arenas of control systems research in the United States between the world wars: naval fire control, the Sperry Gyroscope Company, the Bell Telephone Laboratories, and Vannevar Bush's laboratory at MIT. Each of these institutional sites had unique technical problems, organizational imperatives, and working environments, and each fostered a distinct engineering culture. Each also developed technologies to represent the world in a machine. At the beginning of World War II, President Roosevelt established the National Defense Research Committee, one division of which was devoted to control systems. Mindell shows how the NDRC brought together representatives from the four pre-war engineering cultures, and how its projects synthesized conceptions of control, communications, and computing. By the time Wiener articulated his vision, these ideas were already suffusing through engineering. They would profoundly influence the digital world. As a new way to conceptualize the history of computing, this book will be of great interest to historians of science, technology, and culture, as well as computer scientists and theorists. Between Human and Machine: Feedback, Control, and Computing before Cybernetics
Author: Erik Grafarend
Publisher: Springer Science & Business Media
ISBN: 3642222412
Category : Science
Languages : en
Pages : 1026
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Book Description
Here we present a nearly complete treatment of the Grand Universe of linear and weakly nonlinear regression models within the first 8 chapters. Our point of view is both an algebraic view as well as a stochastic one. For example, there is an equivalent lemma between a best, linear uniformly unbiased estimation (BLUUE) in a Gauss-Markov model and a least squares solution (LESS) in a system of linear equations. While BLUUE is a stochastic regression model, LESS is an algebraic solution. In the first six chapters we concentrate on underdetermined and overdeterimined linear systems as well as systems with a datum defect. We review estimators/algebraic solutions of type MINOLESS, BLIMBE, BLUMBE, BLUUE, BIQUE, BLE, BIQUE and Total Least Squares. The highlight is the simultaneous determination of the first moment and the second central moment of a probability distribution in an inhomogeneous multilinear estimation by the so called E-D correspondence as well as its Bayes design. In addition, we discuss continuous networks versus discrete networks, use of Grassmann-Pluecker coordinates, criterion matrices of type Taylor-Karman as well as FUZZY sets. Chapter seven is a speciality in the treatment of an overdetermined system of nonlinear equations on curved manifolds. The von Mises-Fisher distribution is characteristic for circular or (hyper) spherical data. Our last chapter eight is devoted to probabilistic regression, the special Gauss-Markov model with random effects leading to estimators of type BLIP and VIP including Bayesian estimation. A great part of the work is presented in four Appendices. Appendix A is a treatment, of tensor algebra, namely linear algebra, matrix algebra and multilinear algebra. Appendix B is devoted to sampling distributions and their use in terms of confidence intervals and confidence regions. Appendix C reviews the elementary notions of statistics, namely random events and stochastic processes. Appendix D introduces the basics of Groebner basis algebra, its careful definition, the Buchberger Algorithm, especially the C. F. Gauss combinatorial algorithm.
Author: Bent Jorgensen
Publisher: Routledge
ISBN: 1351408615
Category : Mathematics
Languages : en
Pages : 185
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Book Description
Providing a self-contained exposition of the theory of linear models, this treatise strikes a compromise between theory and practice, providing a sound theoretical basis while putting the theory to work in important cases.
