Download or read book Random Data written by Julius S. Bendat and published by John Wiley & Sons. This book was released on 2011-09-20 with total page 555 pages. Available in PDF, EPUB and Kindle. Book excerpt: RANDOM DATA A TIMELY UPDATE OF THE CLASSIC BOOK ON THE THEORY AND APPLICATION OF RANDOM DATA ANALYSIS First published in 1971, Random Data served as an authoritative book on the analysis of experimental physical data for engineering and scientific applications. This Fourth Edition features coverage of new developments in random data management and analysis procedures that are applicable to a broad range of applied fields, from the aerospace and automotive industries to oceanographic and biomedical research. This new edition continues to maintain a balance of classic theory and novel techniques. The authors expand on the treatment of random data analysis theory, including derivations of key relationships in probability and random process theory. The book remains unique in its practical treatment of nonstationary data analysis and nonlinear system analysis, presenting the latest techniques on modern data acquisition, storage, conversion, and qualification of random data prior to its digital analysis. The Fourth Edition also includes: A new chapter on frequency domain techniques to model and identify nonlinear systems from measured input/output random data New material on the analysis of multiple-input/single-output linear models The latest recommended methods for data acquisition and processing of random data Important mathematical formulas to design experiments and evaluate results of random data analysis and measurement procedures Answers to the problem in each chapter Comprehensive and self-contained, Random Data, Fourth Edition is an indispensible book for courses on random data analysis theory and applications at the upper-under-graduate and graduate level. It is also an insightful reference for engineers and scientists who use statistical methods to investigate and solve problems with dynamic data.

Download or read book Processing Random Data written by Robert V. Edwards and published by World Scientific. This book was released on 2006 with total page 156 pages. Available in PDF, EPUB and Kindle. Book excerpt: Two features of Processing Random Data differentiate it from other similar books: the focus on computing the reproducibility error for statistical measurements, and its comprehensive coverage of Maximum Likelihood parameter estimation techniques. The book is useful for dealing with situations where there is a model relating to the input and output of a process, but with a random component, which could be noise in the system or the process itself could be random, like turbulence. Parameter estimation techniques are shown for many different types of statistical models, including joint Gaussian. The Cramer-Rao bounds are described as useful estimates of reproducibility errors.Finally, using an example with a random sampling of turbulent flows that can occur when using laser anemometry the book also explains the use of conditional probabilities.

Download or read book Processing Random Data Statistics For Engineers And Scientists written by Robert V Edwards and published by World Scientific Publishing Company. This book was released on 2006-07-03 with total page 152 pages. Available in PDF, EPUB and Kindle. Book excerpt: Two features of Processing Random Data differentiate it from other similar books: the focus on computing the reproducibility error for statistical measurements, and its comprehensive coverage of Maximum Likelihood parameter estimation techniques. The book is useful for dealing with situations where there is a model relating to the input and output of a process, but with a random component, which could be noise in the system or the process itself could be random, like turbulence. Parameter estimation techniques are shown for many different types of statistical models, including joint Gaussian. The Cramer-Rao bounds are described as useful estimates of reproducibility errors.Finally, using an example with a random sampling of turbulent flows that can occur when using laser anemometry the book also explains the use of conditional probabilities.

Download or read book Uncertainty quantification for wave propagation and flow problems with random data written by Markus Wahlsten and published by Linköping University Electronic Press. This book was released on 2018-04-09 with total page 26 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this thesis we study partial differential equations with random inputs. The effects that different boundary conditions with random data and uncertain geometries have on the solution are analyzed. Further, comparisons and couplings between different uncertainty quantification methods are performed. The numerical simulations are based on provably strongly stable finite difference formulations based on summation-by-parts operators and a weak implementation of boundary and interface conditions. The first part of this thesis treats the construction of variance reducing boundary conditions. It is shown how the variance of the solution can be manipulated by the choice of boundary conditions, and a close relation between the variance of the solution and the energy estimate is established. The technique is studied on both a purely hyperbolic system as well as an incompletely parabolic system of equations. The applications considered are the Euler, Maxwell's, and Navier--Stokes equations. The second part focuses on the effect of uncertain geometry on the solution. We consider a two-dimensional advection-diffusion equation with a stochastically varying boundary. We transform the problem to a fixed domain where comparisons can be made. Numerical results are performed on a problem in heat transfer, where the frequency and amplitude of the prescribed uncertainty are varied. The final part of the thesis is devoted to the comparison and coupling of different uncertainty quantification methods. An efficiency analysis is performed using the intrusive polynomial chaos expansion with stochastic Galerkin projection, and nonintrusive numerical integration. The techniques are compared using the non-linear viscous Burgers' equation. A provably stable coupling procedure for the two methods is also constructed. The general coupling procedure is exemplified using a hyperbolic system of equations.

Download or read book Innovative Statistical Methods for Public Health Data written by Ding-Geng (Din) Chen and published by Springer. This book was released on 2015-08-31 with total page 351 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book brings together experts working in public health and multi-disciplinary areas to present recent issues in statistical methodological development and their applications. This timely book will impact model development and data analyses of public health research across a wide spectrum of analysis. Data and software used in the studies are available for the reader to replicate the models and outcomes. The fifteen chapters range in focus from techniques for dealing with missing data with Bayesian estimation, health surveillance and population definition and implications in applied latent class analysis, to multiple comparison and meta-analysis in public health data. Researchers in biomedical and public health research will find this book to be a useful reference and it can be used in graduate level classes.

Download or read book A First Course in Random Matrix Theory written by Marc Potters and published by Cambridge University Press. This book was released on 2020-12-03 with total page 371 pages. Available in PDF, EPUB and Kindle. Book excerpt: An intuitive, up-to-date introduction to random matrix theory and free calculus, with real world illustrations and Big Data applications.

Download or read book Random Signals written by K. Sam Shanmugan and published by John Wiley & Sons. This book was released on 1988-05-20 with total page 686 pages. Available in PDF, EPUB and Kindle. Book excerpt: This treatise develops the theory of random processes and its application to the study of systems and the analysis of random data. It covers the fundamentals of random process models, the applications of probabilistic models and statistical estimation.

Download or read book Collecting Spatial Data written by Werner G. Müller and published by Springer Science & Business Media. This book was released on 2007-08-17 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book is concerned with the statistical theory for locating spatial sensors. It bridges the gap between spatial statistics and optimum design theory. After introductions to those two fields the topics of exploratory designs and designs for spatial trend and variogram estimation are treated. Special attention is devoted to describing new methodologies to cope with the problem of correlated observations.

Download or read book Beginning JavaScript Charts written by Fabio Nelli and published by Apress. This book was released on 2014-01-24 with total page 602 pages. Available in PDF, EPUB and Kindle. Book excerpt: Beginning JavaScript Charts shows how to convert your data into eye-catching, innovative, animated, and highly interactive browser-based charts. This book is suitable for developers of all experience levels and needs: for those who love fast and effective solutions, you can use the jqPlot library to generate charts with amazing effects and animations using only a few lines of code; if you want more power and need to create data visualization beyond traditional charts, then D3 is the JavaScript library for you; finally, if you need a high-performance, professional solution for interactive charts, then the Highcharts library is also covered. If you are an experienced developer and want to take things further, then Beginning JavaScript Charts also shows you how to develop your own graphics library starting from scratch using jQuery. At the end of the book, you will have a good knowledge of all the elements needed to manage data from every possible source, from high-end scientific instruments to Arduino boards, from PHP SQL databases queries to simple HTML tables, and from Matlab calculations to reports in Excel. You will be able to provide cutting-edge charts exploiting the growing power of modern browsers. Create all kinds of charts using the latest technologies available on browsers (HTML5, CSS3, jQuery, jqPlot, D3, Highcharts, and SVG) Full of step-by-step examples, Beginning JavaScript Charts introduces you gradually to all aspects of chart development, from the data source to the choice of which solution to apply. This book provides a number of tools that can be the starting point for any project requiring graphical representations of data, whether using commercial libraries or your own

Download or read book Random Fields for Spatial Data Modeling written by Dionissios T. Hristopulos and published by Springer Nature. This book was released on 2020-02-17 with total page 884 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an inter-disciplinary introduction to the theory of random fields and its applications. Spatial models and spatial data analysis are integral parts of many scientific and engineering disciplines. Random fields provide a general theoretical framework for the development of spatial models and their applications in data analysis. The contents of the book include topics from classical statistics and random field theory (regression models, Gaussian random fields, stationarity, correlation functions) spatial statistics (variogram estimation, model inference, kriging-based prediction) and statistical physics (fractals, Ising model, simulated annealing, maximum entropy, functional integral representations, perturbation and variational methods). The book also explores links between random fields, Gaussian processes and neural networks used in machine learning. Connections with applied mathematics are highlighted by means of models based on stochastic partial differential equations. An interlude on autoregressive time series provides useful lower-dimensional analogies and a connection with the classical linear harmonic oscillator. Other chapters focus on non-Gaussian random fields and stochastic simulation methods. The book also presents results based on the author’s research on Spartan random fields that were inspired by statistical field theories originating in physics. The equivalence of the one-dimensional Spartan random field model with the classical, linear, damped harmonic oscillator driven by white noise is highlighted. Ideas with potentially significant computational gains for the processing of big spatial data are presented and discussed. The final chapter concludes with a description of the Karhunen-Loève expansion of the Spartan model. The book will appeal to engineers, physicists, and geoscientists whose research involves spatial models or spatial data analysis. Anyone with background in probability and statistics can read at least parts of the book. Some chapters will be easier to understand by readers familiar with differential equations and Fourier transforms.

Download or read book Statistical Applications for Environmental Analysis and Risk Assessment written by Joseph Ofungwu and published by John Wiley & Sons. This book was released on 2014-05-06 with total page 656 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Applications for Environmental Analysis and Risk Assessment guides readers through real-world situations and the best statistical methods used to determine the nature and extent of the problem, evaluate the potential human health and ecological risks, and design and implement remedial systems as necessary. Featuring numerous worked examples using actual data and “ready-made” software scripts, Statistical Applications for Environmental Analysis and Risk Assessment also includes: • Descriptions of basic statistical concepts and principles in an informal style that does not presume prior familiarity with the subject • Detailed illustrations of statistical applications in the environmental and related water resources fields using real-world data in the contexts that would typically be encountered by practitioners • Software scripts using the high-powered statistical software system, R, and supplemented by USEPA’s ProUCL and USDOE’s VSP software packages, which are all freely available • Coverage of frequent data sample issues such as non-detects, outliers, skewness, sustained and cyclical trend that habitually plague environmental data samples • Clear demonstrations of the crucial, but often overlooked, role of statistics in environmental sampling design and subsequent exposure risk assessment.

Download or read book Perceptual Issues in Visualization written by Georges Grinstein and published by Springer Science & Business Media. This book was released on 2013-03-07 with total page 167 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the increase in the amount and dimensionality of scientific data collected, new approaches to the design of displays of such data have become essential. The designers of visual and auditory displays of scientific data seek to harness perceptual processes for data exploration. The general aim is to provide ways for raw data, and the statistical and mathematical structures they comprise, to "speak for themselves" and, thereby, enable scientists to conduct exploratory, in addition to confirmatory analyses of their data. The present primary approach via visualization depends mainly on coding data as positions of visually distinguishable elements in a two- or three- dimen sional euclidean space, e.g., as discrete points comprising clusters in scatter-plot displays and as patches comprising the hills and valleys of statistical surfaces. These displays are immensely effective because the data are in a form that evokes natural perceptual processing of the data into impressions of the presence and spatial disposition of apparent materials, objects, and structures in the viewers apparent physical environment. The problem with this mode of display, however, is that its perceptual potency is largeiy exhausted at dimension three, while we increasingly face the need to explore data of much greater dimensionality. The challenge posed for visualization researchers is to develop new modes of display that can push the dimensionality of data displays higher while retaining the kind of perceptual potency needed for data exploration.

Download or read book Spectral Analysis of Large Dimensional Random Matrices written by Zhidong Bai and published by Springer Science & Business Media. This book was released on 2009-12-10 with total page 560 pages. Available in PDF, EPUB and Kindle. Book excerpt: The aim of the book is to introduce basic concepts, main results, and widely applied mathematical tools in the spectral analysis of large dimensional random matrices. The core of the book focuses on results established under moment conditions on random variables using probabilistic methods, and is thus easily applicable to statistics and other areas of science. The book introduces fundamental results, most of them investigated by the authors, such as the semicircular law of Wigner matrices, the Marcenko-Pastur law, the limiting spectral distribution of the multivariate F matrix, limits of extreme eigenvalues, spectrum separation theorems, convergence rates of empirical distributions, central limit theorems of linear spectral statistics, and the partial solution of the famous circular law. While deriving the main results, the book simultaneously emphasizes the ideas and methodologies of the fundamental mathematical tools, among them being: truncation techniques, matrix identities, moment convergence theorems, and the Stieltjes transform. Its treatment is especially fitting to the needs of mathematics and statistics graduate students and beginning researchers, having a basic knowledge of matrix theory and an understanding of probability theory at the graduate level, who desire to learn the concepts and tools in solving problems in this area. It can also serve as a detailed handbook on results of large dimensional random matrices for practical users. This second edition includes two additional chapters, one on the authors' results on the limiting behavior of eigenvectors of sample covariance matrices, another on applications to wireless communications and finance. While attempting to bring this edition up-to-date on recent work, it also provides summaries of other areas which are typically considered part of the general field of random matrix theory.

Download or read book Aerospace Instrumentation written by M. A. Perry and published by Elsevier. This book was released on 2015-05-18 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: Aerospace Instrumentation, Volume 4 is a collection of papers presented at the Fourth International Aerospace Instrumentation Symposium, held at the College of Aeronautics, Cranfield. Co-sponsored by the Instrument Society of America, the symposium covers most aspects of aerospace instrumentation. This book is composed of 14 chapters and begins with a description of strain gauge transducers, an introduction to noise, filtering, and random function, as well as the data analysis facility designed to satisfy the needs in the fields of fundamental research and major power plant design and commissioning. A chapter examines equipment for the analysis of random processes for low frequence purposes. Other chapters explore the measurement and analysis of rotor blade airloads, the application of digital computer to instrumentation systems, the features of an altitude test facility, and the trade-offs existing between analogue and digital filtering techniques. The last chapters are devoted to test methods for aircraft performance, stability, and control characteristics determination in non-steady flight. These chapters also treat the operational experience of the B-70 flight test data system. This book will prove useful to aerospace scientists, engineers and research workers.

Download or read book Managing and Processing Big Data in Cloud Computing written by Kannan, Rajkumar and published by IGI Global. This book was released on 2016-01-07 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big data has presented a number of opportunities across industries. With these opportunities come a number of challenges associated with handling, analyzing, and storing large data sets. One solution to this challenge is cloud computing, which supports a massive storage and computation facility in order to accommodate big data processing. Managing and Processing Big Data in Cloud Computing explores the challenges of supporting big data processing and cloud-based platforms as a proposed solution. Emphasizing a number of crucial topics such as data analytics, wireless networks, mobile clouds, and machine learning, this publication meets the research needs of data analysts, IT professionals, researchers, graduate students, and educators in the areas of data science, computer programming, and IT development.

Download or read book A Million Random Digits with 100 000 Normal Deviates written by and published by Minnesota Historical Society. This book was released on 2001 with total page 636 pages. Available in PDF, EPUB and Kindle. Book excerpt: Not long after research began at RAND in 1946, the need arose for random numbers that could be used to solve problems of various kinds of experimental probability procedures. These applications, called Monte Carlo methods, required a large supply of random digits and normal deviates of high quality, and the tables presented here were produced to meet those requirements.This book was a product of RAND's pioneering work in computing, as well a testament to the patience and persistence of researchers in the early days of RAND. The tables of random numbers in this book have become a standard reference in engineering and econometrics textbooks and have been widely used in gaming and simulations that employ Monte Carlo trials. Still the largest published source of random digits and normal deviates, the work is routinely used by statisticians, physicists, polltakers, market analysts, lottery administrators, and quality control engineers. A 2001 article in the New York Times on the value of randomness featured the original edition of the book, published in 1955 by the Free Press. The rights have since reverted to RAND, and in this digital age, we thought it appropriate to reissue a new edition of the book in its original format, with a new foreword by Michael D. Rich, RAND's Executive Vice President

Download or read book Introduction to Data Science written by Rafael A. Irizarry and published by CRC Press. This book was released on 2019-11-20 with total page 794 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction to Data Science: Data Analysis and Prediction Algorithms with R introduces concepts and skills that can help you tackle real-world data analysis challenges. It covers concepts from probability, statistical inference, linear regression, and machine learning. It also helps you develop skills such as R programming, data wrangling, data visualization, predictive algorithm building, file organization with UNIX/Linux shell, version control with Git and GitHub, and reproducible document preparation. This book is a textbook for a first course in data science. No previous knowledge of R is necessary, although some experience with programming may be helpful. The book is divided into six parts: R, data visualization, statistics with R, data wrangling, machine learning, and productivity tools. Each part has several chapters meant to be presented as one lecture. The author uses motivating case studies that realistically mimic a data scientist’s experience. He starts by asking specific questions and answers these through data analysis so concepts are learned as a means to answering the questions. Examples of the case studies included are: US murder rates by state, self-reported student heights, trends in world health and economics, the impact of vaccines on infectious disease rates, the financial crisis of 2007-2008, election forecasting, building a baseball team, image processing of hand-written digits, and movie recommendation systems. The statistical concepts used to answer the case study questions are only briefly introduced, so complementing with a probability and statistics textbook is highly recommended for in-depth understanding of these concepts. If you read and understand the chapters and complete the exercises, you will be prepared to learn the more advanced concepts and skills needed to become an expert.