Introduction to Time Series and Forecasting

Author: Peter J. Brockwell
Publisher: Springer Science & Business Media
ISBN: 1475725264
Format: PDF, ePub
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Some of the key mathematical results are stated without proof in order to make the underlying theory acccessible to a wider audience. The book assumes a knowledge only of basic calculus, matrix algebra, and elementary statistics. The emphasis is on methods and the analysis of data sets. The logic and tools of model-building for stationary and non-stationary time series are developed in detail and numerous exercises, many of which make use of the included computer package, provide the reader with ample opportunity to develop skills in this area. The core of the book covers stationary processes, ARMA and ARIMA processes, multivariate time series and state-space models, with an optional chapter on spectral analysis. Additional topics include harmonic regression, the Burg and Hannan-Rissanen algorithms, unit roots, regression with ARMA errors, structural models, the EM algorithm, generalized state-space models with applications to time series of count data, exponential smoothing, the Holt-Winters and ARAR forecasting algorithms, transfer function models and intervention analysis. Brief introducitons are also given to cointegration and to non-linear, continuous-time and long-memory models. The time series package included in the back of the book is a slightly modified version of the package ITSM, published separately as ITSM for Windows, by Springer-Verlag, 1994. It does not handle such large data sets as ITSM for Windows, but like the latter, runs on IBM-PC compatible computers under either DOS or Windows (version 3.1 or later). The programs are all menu-driven so that the reader can immediately apply the techniques in the book to time series data, with a minimal investment of time in the computational and algorithmic aspects of the analysis.

Theory of Multivariate Statistics

Author: Martin Bilodeau
Publisher: Springer Science & Business Media
ISBN: 9780387987392
Format: PDF, Docs
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This book presents the main results of the modern theory of multivariate statistics for those who need a concise yet mathematically rigorous treatment. Researchers will find it to be an indispensable reference, presenting developments from recent work on broad topics such as robust inference and the bootstrap in a multivariate setting. The treatment is novel and unique in several ways, and will be refreshing to those saturated in a lifetime of matrix derivatives and Jacobians.

Design and Analysis of Experiments

Author: Angela M. Dean
Publisher: Springer Science & Business Media
ISBN: 0387226346
Format: PDF, ePub
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This book offers a step-by-step guide to the experimental planning process and the ensuing analysis of normally distributed data, emphasizing the practical considerations governing the design of an experiment. Data sets are taken from real experiments and sample SAS programs are included with each chapter. Experimental design is an essential part of investigation and discovery in science; this book will serve as a modern and comprehensive reference to the subject.

Plane Answers to Complex Questions

Author: Ronald Christensen
Publisher: Springer Science & Business Media
ISBN: 9780387953618
Format: PDF, ePub, Docs
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This textbook provides a wide-ranging introduction to the use and theory of linear models for analyzing data. The author's emphasis is on providing a unified treatment of linear models, including analysis of variance models and regression models, based on projections, orthogonality, and other vector space ideas. Every chapter comes with numerous exercises and examples that make it ideal for a graduate-level course. All of the standard topics are covered in depth: ANOVA, estimation including Bayesian estimation, hypothesis testing, multiple comparisons, regression analysis, and experimental design models. In addition, the book covers topics that are not usually treated at this level, but which are important in their own right: balanced incomplete block designs, testing for lack of fit, testing for independence, models with singular covariance matrices, variance component estimation, best linear and best linear unbiased prediction, collinearity, and variable selection. This new edition includes discussion of identifiability and its relationship to estimability, different approaches to the theories of testing parametric hypotheses and analysis of covariance, additional discussion of the geometry of least squares estimation and testing, new discussion of models for experiments with factorial treatment structures, and a new appendix on possible causes for getting test statistics that are so small as to be suspicious. Ronald Christensen is a Professor of Statistics at the University of New Mexico. He is a Fellow of the American Statistical Association and the Institute of Mathematical Statistics.

Probability

Author: Jim Pitman
Publisher: Springer Science & Business Media
ISBN: 1461243742
Format: PDF, Mobi
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This is a text for a one-quarter or one-semester course in probability, aimed at students who have done a year of calculus. The book is organised so a student can learn the fundamental ideas of probability from the first three chapters without reliance on calculus. Later chapters develop these ideas further using calculus tools. The book contains more than the usual number of examples worked out in detail. The most valuable thing for students to learn from a course like this is how to pick up a probability problem in a new setting and relate it to the standard body of theory. The more they see this happen in class, and the more they do it themselves in exercises, the better. The style of the text is deliberately informal. My experience is that students learn more from intuitive explanations, diagrams, and examples than they do from theorems and proofs. So the emphasis is on problem solving rather than theory.

Statistical Analysis and Data Display

Author: Richard M. Heiberger
Publisher: Springer Science & Business Media
ISBN: 1475742843
Format: PDF
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This presentation of statistical methods features extensive use of graphical displays for exploring data and for displaying the analysis. The authors demonstrate how to analyze data—showing code, graphics, and accompanying computer listings. They emphasize how to construct and interpret graphs, discuss principles of graphical design, and show how tabular results are used to confirm the visual impressions derived from the graphs. Many of the graphical formats are novel and appear here for the first time in print.

Probability Theory

Author: Yuan Shih Chow
Publisher: Springer Science & Business Media
ISBN: 9780387406077
Format: PDF, Mobi
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Now in paperback, this text covers major theorems of probability theory and the measure theoretical foundations of the subject. Main topics treated are independence, interchangeability, and martingales, with special emphasis on stopping time, both as tools in proving theorems and as objects of interest themselves. This edition contains much new material, such as U-statistic, additional theorems and examples, and simpler versions of some proofs.