Read Books Online and Download eBooks, EPub, PDF, Mobi, Kindle, Text Full Free.
State Space Model And Smoothing Algorithm To Solve A Missing Data Problem In Spatial Temporal Series
Download State Space Model And Smoothing Algorithm To Solve A Missing Data Problem In Spatial Temporal Series full books in PDF, epub, and Kindle. Read online State Space Model And Smoothing Algorithm To Solve A Missing Data Problem In Spatial Temporal Series ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Book Synopsis State space model and smoothing algorithm to solve a missing data problem in spatial temporal series by : Luigi Ippoliti
Download or read book State space model and smoothing algorithm to solve a missing data problem in spatial temporal series written by Luigi Ippoliti and published by . This book was released on 1998 with total page 11 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Fixed Interval Smoothing for State Space Models by : Howard L. Weinert
Download or read book Fixed Interval Smoothing for State Space Models written by Howard L. Weinert and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 126 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fixed-interval smoothing is a method of extracting useful information from inaccurate data. It has been applied to problems in engineering, the physical sciences, and the social sciences, in areas such as control, communications, signal processing, acoustics, geophysics, oceanography, statistics, econometrics, and structural analysis. This monograph addresses problems for which a linear stochastic state space model is available, in which case the objective is to compute the linear least-squares estimate of the state vector in a fixed interval, using observations previously collected in that interval. The author uses a geometric approach based on the method of complementary models. Using the simplest possible notation, he presents straightforward derivations of the four types of fixed-interval smoothing algorithms, and compares the algorithms in terms of efficiency and applicability. Results show that the best algorithm has received the least attention in the literature. Fixed Interval Smoothing for State Space Models: includes new material on interpolation, fast square root implementations, and boundary value models; is the first book devoted to smoothing; contains an annotated bibliography of smoothing literature; uses simple notation and clear derivations; compares algorithms from a computational perspective; identifies a best algorithm. Fixed Interval Smoothing for State Space Models will be the primary source for those wanting to understand and apply fixed-interval smoothing: academics, researchers, and graduate students in control, communications, signal processing, statistics and econometrics.
Book Synopsis Modeling Data in Time and Space - Studies of Irregularities, Dependence Structure and Applications by : Huy Dang
Download or read book Modeling Data in Time and Space - Studies of Irregularities, Dependence Structure and Applications written by Huy Dang and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation is a compilation of three research projects on the analysis of data in time and space. The first and second projects propose approaches for the analysis of longitudinal and spatio-temporal data that comprise irregularities, and the third project proposes an integrated approach for capturing the spatio-temporal dependence structure of spatially organized time series. In the first project, we propose a method that, combining an EM algorithm with penalized smoothing, can simultaneously estimate the smooth component and detect irregular spikes in a 1-dimensional signal. Imposing some assumptions on the error distribution, we study consistency of EM updates when some or all parameters are unknown. Robustness of the proposed method to assumptions violations is ascertained via simulations. The second project is motivated by a specific application in functional magnetic resonance imaging (fMRI); namely, head motion detection. Head motion can be viewed as an abrupt change in fMRI signals that are otherwise a smooth function of brain activities in time. By transforming the data to wavelet space, and studying the decay rate of wavelet coefficients across different scales, we are able to estimate the local smoothness of data in three dimensions (a 2-dimensional brain slice and time) and identify local irregularities. In the third project, we study the complex spatio-temporal dependence structure of cortical surface fMRI data. Specifically, we model the non-stationary dependence of activation patterns across the cortical surface via a stochastic differential equation prior. Moreover, we provide evidence of varying ranges of temporal dependence across different brain regions, and model such dependence as fractional Gaussian noise of varying Hurst parameters. The result is a fully integrated, efficient framework that considers spatial and temporal dependence structure simultaneously, and is computationally viable.
Book Synopsis Scientific and Technical Aerospace Reports by :
Download or read book Scientific and Technical Aerospace Reports written by and published by . This book was released on 1995 with total page 704 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Bayesian Filtering and Smoothing by : Simo Särkkä
Download or read book Bayesian Filtering and Smoothing written by Simo Särkkä and published by Cambridge University Press. This book was released on 2013-09-05 with total page 255 pages. Available in PDF, EPUB and Kindle. Book excerpt: A unified Bayesian treatment of the state-of-the-art filtering, smoothing, and parameter estimation algorithms for non-linear state space models.
Book Synopsis Flexible Imputation of Missing Data, Second Edition by : Stef van Buuren
Download or read book Flexible Imputation of Missing Data, Second Edition written by Stef van Buuren and published by CRC Press. This book was released on 2018-07-17 with total page 444 pages. Available in PDF, EPUB and Kindle. Book excerpt: Missing data pose challenges to real-life data analysis. Simple ad-hoc fixes, like deletion or mean imputation, only work under highly restrictive conditions, which are often not met in practice. Multiple imputation replaces each missing value by multiple plausible values. The variability between these replacements reflects our ignorance of the true (but missing) value. Each of the completed data set is then analyzed by standard methods, and the results are pooled to obtain unbiased estimates with correct confidence intervals. Multiple imputation is a general approach that also inspires novel solutions to old problems by reformulating the task at hand as a missing-data problem. This is the second edition of a popular book on multiple imputation, focused on explaining the application of methods through detailed worked examples using the MICE package as developed by the author. This new edition incorporates the recent developments in this fast-moving field. This class-tested book avoids mathematical and technical details as much as possible: formulas are accompanied by verbal statements that explain the formula in accessible terms. The book sharpens the reader’s intuition on how to think about missing data, and provides all the tools needed to execute a well-grounded quantitative analysis in the presence of missing data.
Book Synopsis Soil Spatial Variability by : Donald R. Nielsen
Download or read book Soil Spatial Variability written by Donald R. Nielsen and published by Bernan Press(PA). This book was released on 1985 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: ISSS congress geostatistics
Book Synopsis Index to Theses with Abstracts Accepted for Higher Degrees by the Universities of Great Britain and Ireland and the Council for National Academic Awards by :
Download or read book Index to Theses with Abstracts Accepted for Higher Degrees by the Universities of Great Britain and Ireland and the Council for National Academic Awards written by and published by . This book was released on 2008 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Handbook of Mathematical Geosciences by : B.S. Daya Sagar
Download or read book Handbook of Mathematical Geosciences written by B.S. Daya Sagar and published by Springer. This book was released on 2018-06-25 with total page 911 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Open Access handbook published at the IAMG's 50th anniversary, presents a compilation of invited path-breaking research contributions by award-winning geoscientists who have been instrumental in shaping the IAMG. It contains 45 chapters that are categorized broadly into five parts (i) theory, (ii) general applications, (iii) exploration and resource estimation, (iv) reviews, and (v) reminiscences covering related topics like mathematical geosciences, mathematical morphology, geostatistics, fractals and multifractals, spatial statistics, multipoint geostatistics, compositional data analysis, informatics, geocomputation, numerical methods, and chaos theory in the geosciences.
Book Synopsis State-Space System Realization with Input- and Output-Data Correlation by : Jer-Nan Juang
Download or read book State-Space System Realization with Input- and Output-Data Correlation written by Jer-Nan Juang and published by . This book was released on 1997 with total page 48 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Spatial AutoRegression (SAR) Model by : Baris M. Kazar
Download or read book Spatial AutoRegression (SAR) Model written by Baris M. Kazar and published by Springer Science & Business Media. This book was released on 2012-03-02 with total page 81 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explosive growth in the size of spatial databases has highlighted the need for spatial data mining techniques to mine the interesting but implicit spatial patterns within these large databases. This book explores computational structure of the exact and approximate spatial autoregression (SAR) model solutions. Estimation of the parameters of the SAR model using Maximum Likelihood (ML) theory is computationally very expensive because of the need to compute the logarithm of the determinant (log-det) of a large matrix in the log-likelihood function. The second part of the book introduces theory on SAR model solutions. The third part of the book applies parallel processing techniques to the exact SAR model solutions. Parallel formulations of the SAR model parameter estimation procedure based on ML theory are probed using data parallelism with load-balancing techniques. Although this parallel implementation showed scalability up to eight processors, the exact SAR model solution still suffers from high computational complexity and memory requirements. These limitations have led the book to investigate serial and parallel approximate solutions for SAR model parameter estimation. In the fourth and fifth parts of the book, two candidate approximate-semi-sparse solutions of the SAR model based on Taylor's Series expansion and Chebyshev Polynomials are presented. Experiments show that the differences between exact and approximate SAR parameter estimates have no significant effect on the prediction accuracy. In the last part of the book, we developed a new ML based approximate SAR model solution and its variants in the next part of the thesis. The new approximate SAR model solution is called the Gauss-Lanczos approximated SAR model solution. We algebraically rank the error of the Chebyshev Polynomial approximation, Taylor's Series approximation and the Gauss-Lanczos approximation to the solution of the SAR model and its variants. In other words, we established a novel relationship between the error in the log-det term, which is the approximated term in the concentrated log-likelihood function and the error in estimating the SAR parameter for all of the approximate SAR model solutions.
Book Synopsis Population Dynamics in Variable Environments by : Shripad Tuljapurkar
Download or read book Population Dynamics in Variable Environments written by Shripad Tuljapurkar and published by Springer Science & Business Media. This book was released on 2013-04-17 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt: Demography relates observable facts about individuals to the dynamics of populations. If the dynamics are linear and do not change over time, the classical theory of Lotka (1907) and Leslie (1945) is the central tool of demography. This book addresses the situation when the assumption of constancy is dropped. In many practical situations, a population will display unpredictable variation over time in its vital rates, which must then be described in statistical terms. Most of this book is concerned with the theory of populations which are subject to random temporal changes in their vital rates, although other kinds of variation (e. g. , cyclical) are also dealt with. The central questions are: how does temporal variation work its way into a population's future, and how does it affect our interpretation of a population's past. The results here are directed at demographers of humans and at popula tion biologists. The uneven mathematical level is dictated by the material, but the book should be accessible to readers interested in population the ory. (Readers looking for background or prerequisites will find much of it in Hal Caswell's Matrix population models: construction, analysis, and in terpretation (Sinauer 1989) ). This book is in essence a progress report and is deliberately brief; I hope that it is not mystifying. I have not attempted to be complete about either the history or the subject, although most sig nificant results and methods are presented.
Book Synopsis State Space Analysis by : LaMar K. Timothy
Download or read book State Space Analysis written by LaMar K. Timothy and published by . This book was released on 1968 with total page 424 pages. Available in PDF, EPUB and Kindle. Book excerpt: Problems after each chapter
Book Synopsis AMSTAT News by : American Statistical Association
Download or read book AMSTAT News written by American Statistical Association and published by . This book was released on 2003 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Theoretical Aspects of Spatial-Temporal Modeling by : Gareth William Peters
Download or read book Theoretical Aspects of Spatial-Temporal Modeling written by Gareth William Peters and published by Springer. This book was released on 2015-12-24 with total page 136 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a modern introductory tutorial on specialized theoretical aspects of spatial and temporal modeling. The areas covered involve a range of topics which reflect the diversity of this domain of research across a number of quantitative disciplines. For instance, the first chapter provides up-to-date coverage of particle association measures that underpin the theoretical properties of recently developed random set methods in space and time otherwise known as the class of probability hypothesis density framework (PHD filters). The second chapter gives an overview of recent advances in Monte Carlo methods for Bayesian filtering in high-dimensional spaces. In particular, the chapter explains how one may extend classical sequential Monte Carlo methods for filtering and static inference problems to high dimensions and big-data applications. The third chapter presents an overview of generalized families of processes that extend the class of Gaussian process models to heavy-tailed families known as alpha-stable processes. In particular, it covers aspects of characterization via the spectral measure of heavy-tailed distributions and then provides an overview of their applications in wireless communications channel modeling. The final chapter concludes with an overview of analysis for probabilistic spatial percolation methods that are relevant in the modeling of graphical networks and connectivity applications in sensor networks, which also incorporate stochastic geometry features.
Book Synopsis Spatio-Temporal Statistics with R by : Christopher K. Wikle
Download or read book Spatio-Temporal Statistics with R written by Christopher K. Wikle and published by CRC Press. This book was released on 2019-02-18 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: The world is becoming increasingly complex, with larger quantities of data available to be analyzed. It so happens that much of these "big data" that are available are spatio-temporal in nature, meaning that they can be indexed by their spatial locations and time stamps. Spatio-Temporal Statistics with R provides an accessible introduction to statistical analysis of spatio-temporal data, with hands-on applications of the statistical methods using R Labs found at the end of each chapter. The book: Gives a step-by-step approach to analyzing spatio-temporal data, starting with visualization, then statistical modelling, with an emphasis on hierarchical statistical models and basis function expansions, and finishing with model evaluation Provides a gradual entry to the methodological aspects of spatio-temporal statistics Provides broad coverage of using R as well as "R Tips" throughout. Features detailed examples and applications in end-of-chapter Labs Features "Technical Notes" throughout to provide additional technical detail where relevant Supplemented by a website featuring the associated R package, data, reviews, errata, a discussion forum, and more The book fills a void in the literature and available software, providing a bridge for students and researchers alike who wish to learn the basics of spatio-temporal statistics. It is written in an informal style and functions as a down-to-earth introduction to the subject. Any reader familiar with calculus-based probability and statistics, and who is comfortable with basic matrix-algebra representations of statistical models, would find this book easy to follow. The goal is to give as many people as possible the tools and confidence to analyze spatio-temporal data.
Book Synopsis Forecasting, Structural Time Series Models and the Kalman Filter by : Andrew C. Harvey
Download or read book Forecasting, Structural Time Series Models and the Kalman Filter written by Andrew C. Harvey and published by Cambridge University Press. This book was released on 1990 with total page 574 pages. Available in PDF, EPUB and Kindle. Book excerpt: A synthesis of concepts and materials, that ordinarily appear separately in time series and econometrics literature, presents a comprehensive review of theoretical and applied concepts in modeling economic and social time series.
