Read Books Online and Download eBooks, EPub, PDF, Mobi, Kindle, Text Full Free.
Practical Smoothing
Download Practical Smoothing full books in PDF, epub, and Kindle. Read online Practical Smoothing ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Book Synopsis Practical Smoothing by : Paul H.C. Eilers
Download or read book Practical Smoothing written by Paul H.C. Eilers and published by Cambridge University Press. This book was released on 2021-03-18 with total page 213 pages. Available in PDF, EPUB and Kindle. Book excerpt: This user guide presents a popular smoothing tool with practical applications in machine learning, engineering, and statistics.
Book Synopsis multigrid methods by : Stephen F. Mccormick
Download or read book multigrid methods written by Stephen F. Mccormick and published by CRC Press. This book was released on 2020-08-12 with total page 668 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a collection of research papers on a wide variety of multigrid topics, including applications, computation and theory. It represents proceedings of the Third Copper Mountain Conference on Multigrid Methods, which was held at Copper Mountain, Colorado.
Book Synopsis Forecasting: principles and practice by : Rob J Hyndman
Download or read book Forecasting: principles and practice written by Rob J Hyndman and published by OTexts. This book was released on 2018-05-08 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: Forecasting is required in many situations. Stocking an inventory may require forecasts of demand months in advance. Telecommunication routing requires traffic forecasts a few minutes ahead. Whatever the circumstances or time horizons involved, forecasting is an important aid in effective and efficient planning. This textbook provides a comprehensive introduction to forecasting methods and presents enough information about each method for readers to use them sensibly.
Book Synopsis Optimal Estimation of Dynamic Systems by : John L. Crassidis
Download or read book Optimal Estimation of Dynamic Systems written by John L. Crassidis and published by CRC Press. This book was released on 2011-10-26 with total page 745 pages. Available in PDF, EPUB and Kindle. Book excerpt: An ideal self-study guide for practicing engineers as well as senior undergraduate and beginning graduate students, this book highlights the importance of both physical and numerical modeling in solving dynamics-based estimation problems found in engineering systems, such as spacecraft attitude determination, GPS navigation, orbit determination, and aircraft tracking. With more than 100 pages of new material, this reorganized and expanded edition incorporates new theoretical results, a new chapter on advanced sequential state estimation, and additional examples and exercises. MATLAB codes are available on the book's website.
Book Synopsis Multiple Imputation of Missing Data in Practice by : Yulei He
Download or read book Multiple Imputation of Missing Data in Practice written by Yulei He and published by CRC Press. This book was released on 2021-11-20 with total page 419 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multiple Imputation of Missing Data in Practice: Basic Theory and Analysis Strategies provides a comprehensive introduction to the multiple imputation approach to missing data problems that are often encountered in data analysis. Over the past 40 years or so, multiple imputation has gone through rapid development in both theories and applications. It is nowadays the most versatile, popular, and effective missing-data strategy that is used by researchers and practitioners across different fields. There is a strong need to better understand and learn about multiple imputation in the research and practical community. Accessible to a broad audience, this book explains statistical concepts of missing data problems and the associated terminology. It focuses on how to address missing data problems using multiple imputation. It describes the basic theory behind multiple imputation and many commonly-used models and methods. These ideas are illustrated by examples from a wide variety of missing data problems. Real data from studies with different designs and features (e.g., cross-sectional data, longitudinal data, complex surveys, survival data, studies subject to measurement error, etc.) are used to demonstrate the methods. In order for readers not only to know how to use the methods, but understand why multiple imputation works and how to choose appropriate methods, simulation studies are used to assess the performance of the multiple imputation methods. Example datasets and sample programming code are either included in the book or available at a github site (https://github.com/he-zhang-hsu/multiple_imputation_book). Key Features Provides an overview of statistical concepts that are useful for better understanding missing data problems and multiple imputation analysis Provides a detailed discussion on multiple imputation models and methods targeted to different types of missing data problems (e.g., univariate and multivariate missing data problems, missing data in survival analysis, longitudinal data, complex surveys, etc.) Explores measurement error problems with multiple imputation Discusses analysis strategies for multiple imputation diagnostics Discusses data production issues when the goal of multiple imputation is to release datasets for public use, as done by organizations that process and manage large-scale surveys with nonresponse problems For some examples, illustrative datasets and sample programming code from popular statistical packages (e.g., SAS, R, WinBUGS) are included in the book. For others, they are available at a github site (https://github.com/he-zhang-hsu/multiple_imputation_book)
Book Synopsis Advances In Numerical Heat Transfer by : W. Minkowycz
Download or read book Advances In Numerical Heat Transfer written by W. Minkowycz and published by CRC Press. This book was released on 1996-11-01 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first volume in the series. It analyzes several fundamental methodology issues in numerical heat transfer and fluid flow and identifies certain areas of active application. The finite-volume approach is presented with the finite-element methods as well as with energy balance analysis. Applications include the latest development in turbulence modeling and current approaches to inverse problems.
Book Synopsis I. J. Schoenberg Selected Papers by : Boor
Download or read book I. J. Schoenberg Selected Papers written by Boor and published by Springer Science & Business Media. This book was released on 2013-12-11 with total page 445 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Kernel Smoothing in MATLAB by : Ivana Horová
Download or read book Kernel Smoothing in MATLAB written by Ivana Horová and published by World Scientific. This book was released on 2012 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary: Offers a comprehensive overview of statistical theory and emphases the implementation of presented methods in Matlab. This title contains various Matlab scripts useful for kernel smoothing of density, cumulative distribution function, regression function, hazard function, indices of quality and bivariate density.
Book Synopsis Multigrid Methods by : Ulrich Trottenberg
Download or read book Multigrid Methods written by Ulrich Trottenberg and published by Academic Press. This book was released on 2001 with total page 652 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematics of Computing -- Numerical Analysis.
Book Synopsis Nonparametric Models for Longitudinal Data by : Colin O. Wu
Download or read book Nonparametric Models for Longitudinal Data written by Colin O. Wu and published by CRC Press. This book was released on 2018-05-23 with total page 552 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nonparametric Models for Longitudinal Data with Implementations in R presents a comprehensive summary of major advances in nonparametric models and smoothing methods with longitudinal data. It covers methods, theories, and applications that are particularly useful for biomedical studies in the era of big data and precision medicine. It also provides flexible tools to describe the temporal trends, covariate effects and correlation structures of repeated measurements in longitudinal data. This book is intended for graduate students in statistics, data scientists and statisticians in biomedical sciences and public health. As experts in this area, the authors present extensive materials that are balanced between theoretical and practical topics. The statistical applications in real-life examples lead into meaningful interpretations and inferences. Features: Provides an overview of parametric and semiparametric methods Shows smoothing methods for unstructured nonparametric models Covers structured nonparametric models with time-varying coefficients Discusses nonparametric shared-parameter and mixed-effects models Presents nonparametric models for conditional distributions and functionals Illustrates implementations using R software packages Includes datasets and code in the authors’ website Contains asymptotic results and theoretical derivations
Book Synopsis Numerical Treatment of the Navier-Stokes Equations by : Wolfgang Hackbusch
Download or read book Numerical Treatment of the Navier-Stokes Equations written by Wolfgang Hackbusch and published by Vieweg+teubner Verlag. This book was released on 1990 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: The most frequently used method for the numerical integration of parabolic differential equa tions is the method of lines, where one first uses a discretization of space derivatives by finite differences or finite elements and then uses some time-stepping method for the the solution of resulting system of ordinary differential equations. Such methods are, at least conceptually, easy to perform. However, they can be expensive if steep gradients occur in the solution, stability must be controlled, and the global error control can be troublesome. This paper considers a simultaneaus discretization of space and time variables for a one-dimensional parabolic equation on a relatively long time interval, called 'time-slab'. The discretization is repeated or adjusted for following 'time-slabs' using continuous finite element approximations. In such a method we utilize the efficiency of finite elements by choosing a finite element mesh in the time-space domain where the finite element mesh has been adjusted to steep gradients of the solution both with respect to the space and the time variables. In this way we solve all the difficulties with the classical approach since stability, discretization error estimates and global error control are automatically satisfied. Such a method has been discussed previously in [3] and [4]. The related boundary value techniques or global time integration for systems of ordinary differential equations have been discussed in several papers, see [12] and the references quoted therein.
Book Synopsis Introduction to Time Series Modeling with Applications in R by : Genshiro Kitagawa
Download or read book Introduction to Time Series Modeling with Applications in R written by Genshiro Kitagawa and published by CRC Press. This book was released on 2020-08-10 with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the first edition: [This book] reflects the extensive experience and significant contributions of the author to non-linear and non-Gaussian modeling. ... [It] is a valuable book, especially with its broad and accessible introduction of models in the state-space framework. –Statistics in Medicine What distinguishes this book from comparable introductory texts is the use of state-space modeling. Along with this come a number of valuable tools for recursive filtering and smoothing, including the Kalman filter, as well as non-Gaussian and sequential Monte Carlo filters. –MAA Reviews Introduction to Time Series Modeling with Applications in R, Second Edition covers numerous stationary and nonstationary time series models and tools for estimating and utilizing them. The goal of this book is to enable readers to build their own models to understand, predict and master time series. The second edition makes it possible for readers to reproduce examples in this book by using the freely available R package TSSS to perform computations for their own real-world time series problems. This book employs the state-space model as a generic tool for time series modeling and presents the Kalman filter, the non-Gaussian filter and the particle filter as convenient tools for recursive estimation for state-space models. Further, it also takes a unified approach based on the entropy maximization principle and employs various methods of parameter estimation and model selection, including the least squares method, the maximum likelihood method, recursive estimation for state-space models and model selection by AIC. Along with the standard stationary time series models, such as the AR and ARMA models, the book also introduces nonstationary time series models such as the locally stationary AR model, the trend model, the seasonal adjustment model, the time-varying coefficient AR model and nonlinear non-Gaussian state-space models. About the Author: Genshiro Kitagawa is a project professor at the University of Tokyo, the former Director-General of the Institute of Statistical Mathematics, and the former President of the Research Organization of Information and Systems.
Book Synopsis Applied Electrotechnology for Engineers by : C.H. Laycock
Download or read book Applied Electrotechnology for Engineers written by C.H. Laycock and published by Springer. This book was released on 1976-09-01 with total page 303 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Regression written by Ludwig Fahrmeir and published by Springer Nature. This book was released on 2022-03-15 with total page 759 pages. Available in PDF, EPUB and Kindle. Book excerpt: Now in its second edition, this textbook provides an applied and unified introduction to parametric, nonparametric and semiparametric regression that closes the gap between theory and application. The most important models and methods in regression are presented on a solid formal basis, and their appropriate application is shown through numerous examples and case studies. The most important definitions and statements are concisely summarized in boxes, and the underlying data sets and code are available online on the book’s dedicated website. Availability of (user-friendly) software has been a major criterion for the methods selected and presented. The chapters address the classical linear model and its extensions, generalized linear models, categorical regression models, mixed models, nonparametric regression, structured additive regression, quantile regression and distributional regression models. Two appendices describe the required matrix algebra, as well as elements of probability calculus and statistical inference. In this substantially revised and updated new edition the overview on regression models has been extended, and now includes the relation between regression models and machine learning, additional details on statistical inference in structured additive regression models have been added and a completely reworked chapter augments the presentation of quantile regression with a comprehensive introduction to distributional regression models. Regularization approaches are now more extensively discussed in most chapters of the book. The book primarily targets an audience that includes students, teachers and practitioners in social, economic, and life sciences, as well as students and teachers in statistics programs, and mathematicians and computer scientists with interests in statistical modeling and data analysis. It is written at an intermediate mathematical level and assumes only knowledge of basic probability, calculus, matrix algebra and statistics.
Book Synopsis Liquor Store Theatre by : Maya Stovall
Download or read book Liquor Store Theatre written by Maya Stovall and published by Duke University Press. This book was released on 2020-10-09 with total page 211 pages. Available in PDF, EPUB and Kindle. Book excerpt: For six years Maya Stovall staged Liquor Store Theatre, a conceptual art and anthropology video project---included in the Whitney Biennial in 2017---in which she danced near the liquor stores in her Detroit neighborhood as a way to start conversations with her neighbors. In this book of the same name, Stovall uses the project as a point of departure for understanding everyday life in Detroit and the possibilities for ethnographic research, art, and knowledge creation. Her conversations with her neighbors—which touch on everything from economics, aesthetics, and sex to the political and economic racism that undergirds Detroit's history—bring to light rarely acknowledged experiences of longtime Detroiters. In these exchanges, Stovall enacts an innovative form of ethnographic engagement that offers new modes of integrating the social sciences with the arts in ways that exceed what either approach can achieve alone.
Book Synopsis Modern Practical Joinery by : George Ellis
Download or read book Modern Practical Joinery written by George Ellis and published by . This book was released on 1908 with total page 614 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Generalized Additive Models for Location, Scale and Shape by : Mikis D. Stasinopoulos
Download or read book Generalized Additive Models for Location, Scale and Shape written by Mikis D. Stasinopoulos and published by Cambridge University Press. This book was released on 2024-02-29 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive presentation of generalized additive models for location, scale and shape linking methods with diverse applications.
