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"This book provides a hands-on practical guide to using the most suitable models for analysis of statistical data sets using EViews - an interactive Windows-based computer software program for sophisticated data analysis, regression, and forecasting - to define and test statistical hypotheses. Rich in examples and with an emphasis on how to develop acceptable statistical models, Time Series Data Analysis Using EViews is a perfect complement to theoretical books presenting statistical or econometric models for time series data. The procedures introduced are easily extedible to cross-section data sets." "An essential tool for advanced undergraduate and graduate students taking finance or econometrics courses. Statistics, life sciences, and social science students, as well as applied researchers, will also find this book an invaluable resource."--Jacket

Front Matter -- Introduction / Daniel Pęa, George C Tiao -- Basic Concepts in Univariate Time Series. Univariate Time Series: Autocorrelation, Linear Prediction, Spectrum, and State-Space Model / G Tunnicliffe Wilson -- Univariate Autoregressive Moving-Average Models / George C Tiao -- Model Fitting and Checking, and the Kalman Filter / G Tunnicliffe Wilson -- Prediction and Model Selection / Daniel Pęa -- Outliers, Influential Observations, and Missing Data / Daniel Pęa -- Automatic Modeling Methods for Univariate Series / Victor G̤mez, Agust̕n Maravall -- Seasonal Adjustment and Signal Extraction Time Series / Victor G̤mez, Agust̕n Maravall -- Advanced Topics in Univariate Time Series. Heteroscedastic Models / Ruey S Tsay -- Nonlinear Time Series Models: Testing and Applications / Ruey S Tsay -- Bayesian Time Series Analysis / Ruey S Tsay -- Nonparametric Time Series Analysis: Nonparametric Regression, Locally Weighted Regression, Autoregression, and Quantile Regression / Siegfried Heiler -- Neural Network Models / Kurt Hornik, Friedrich Leisch -- Multivariate Time Series. Vector ARMA Models / George C Tiao -- Cointegration in the VAR Model / S̜ren Johansen -- Identification of Linear Dynamic Multiinput/Multioutput Systems / Manfred Deistler -- Index -- Wiley Series in Probability and Statistics.

Good graphs make complex problems clear. From the weather forecast to the Dow Jones average, graphs are so ubiquitous today that it is hard to imagine a world without them. Yet they are a modern invention. This book is the first to comprehensively plot humankind's fascinating efforts to visualize data, from a key seventeenth-century precursor--England's plague-driven initiative to register vital statistics--right up to the latest advances. In a highly readable, richly illustrated story of invention and inventor that mixes science and politics, intrigue and scandal, revolution and shopping

"Introduction to Stochastic Search and Optimization: Estimation, Simulation, and Control is a graduate-level introduction to the principles, algorithms, and practical aspects of stochastic optimization, including applications drawn from engineering, statistics, and computer science. The treatment is both rigorous and broadly accessible, distinguishing this text from much of the current literature and providing students, researchers, and practitioners with a strong foundation for the often-daunting task of solving real-world problems." "The book includes over 130 examples, Web links to software and data sets, more than 250 exercises for the reader, and an extensive list of references. These features help make the text an invaluable resource for those interested in the theory or practice of stochastic search and optimization."--Jacket

An effective technique for data analysis in the social sciencesThe recent explosion in longitudinal data in the social sciences highlights the need for this timely publication. Latent Curve Models: A Structural Equation Perspective provides an effective technique to analyze latent curve models (LCMs). This type of data features random intercepts and slopes that permit each case in a sample to have a different trajectory over time. Furthermore, researchers can include variables to predict the parameters governing these trajectories. The authors synthesize a vast amount of research and findings a

Introduction : distributions and inference for categorical data -- Describing contingency tables -- Inference for contingency tables -- Introduction to generalized linear models -- Logistic regression -- Building and applying logistic regression models -- Logit models for multinomial responses -- Loglinear models for contingency tables -- Building and extending loglinear/logit models -- Models for matched pairs -- Analyzing repeated categorical response data -- Random effects : generalized linear mixed models for categorical responses -- Other mixture models for categorical data -- Asymptotic theory for parametric models -- Alternative estimation theory for parametric models -- Historical tour of categorical data analysis.

Introduction -- Contingency tables -- Generalized linear models -- Logistic regression -- Building and applying logistic regression models -- Multicategory logit models -- Loglinear models for contingency tables -- Models for matched pairs -- Modeling correlated, clustered responses -- Random effects : generalized linear mixed models -- A historical tour of categorical data analysis -- Appendix A. Software for categorical data analysis -- Appendix B. Chi-squared distribution values.

A complete, hands-on guide to the use of statistical methods for obtaining reliable and practical survey research. Applied Survey Methods provides a comprehensive outline of the complete survey process, from design to publication. Filling a gap in the current literature, this one-of-a-kind book describes both the theory and practical applications of survey research with an emphasis on the statistical aspects of survey methods. The book begins with a brief historic overview of survey research methods followed by a discussion that details the needed first steps for carrying out a survey, includi

Simulation and Monte Carlo; Contents; Preface; Glossary; 1 Introduction to simulation and Monte Carlo; 2 Uniform random numbers; 3 General methods for generating random variates; 4 Generation of variates from standard distributions; 5 Variance reduction; 6 Simulation and finance; 7 Discrete event simulation; 8 Markov chain Monte Carlo; 9 Solutions; Appendix 1: Solutions to problems in Chapter 1; Appendix 2: Random number generators; Appendix 3: Computations of acceptance probabilities; Appendix 4: Random variate generators (standard distributions); Appendix 5: Variance reduction.

Bayesian methods are increasingly being used in the social sciences, as the problems encountered lend themselves so naturally to the subjective qualities of Bayesian methodology. This book provides an accessible introduction to Bayesian methods, tailored specifically for social science students. It contains lots of real examples from political science, psychology, sociology, and economics, exercises in all chapters, and detailed descriptions of all the key concepts, without assuming any background in statistics beyond a first course. It features examples of how to implement the methods using W

"Applied Multiway Data Analysis presents a unique, thorough, and authoritative treatment of this relatively new and emerging approach to data analysis that is applicable across a range of fields, from the social and behavioral sciences to agriculture, environmental sciences, and chemistry. General introductions to multiway data types, methods, and estimation procedures are provided in addition to detailed explanations and advice for readers who would like to learn more about applying multiway methods. Using carefully laid out examples and engaging applications, the book begins with an introductory chapter that serves as a general overview of multiway analysis, including the types of problems it can address. Next, the process of setting up, carrying out, and evaluating multiway analyses is discussed along with commonly-encountered issues, such as preprocessing, missing data, model and dimensionality selection, postprocessing, transformation, as well as robustness and stability issues"--Provided by publisher

The Institute Vienna Circle held a conference in Vienna in 2003, Cambridge and Vienna - Frank P. Ramsey and the Vienna Circle, to commemorate the philosophical and scientific work of Frank Plumpton Ramsey (1903-1930). This Ramsey conference provided not only historical and biographical perspectives on one of the most gifted thinkers of the Twentieth Century, but also new impulses for further research on at least some of the topics pioneered by Ramsey, whose interest and potential are greater than ever. Ramsey did pioneering work in several fields, practitioners of which rarely know of his important work in other fields: philosophy of logic and theory of language, foundations of mathematics, mathematics, probability theory, methodology of science, philosophy of psychology, and economics. There was a focus on the one topic which was of strongest mutual concern to Ramsey and the Vienna Circle, namely the question of foundations of mathematics, in particular the status of logicism. Although the major scientific connection linking Ramsey with Austria is his work on logic, to which the Vienna Circle dedicated several meetings, certainly the connection which is of greater general interest concerns Ramsey's visits and discussions with Wittgenstein. Ramsey was the only important thinker to actually visit Wittgenstein during his school-teaching career in Puchberg and Ottertal in the 1920s, in Lower Austria, and later, Ramsey was instrumental in getting Wittgenstein positions at Cambridge.