Author: Konstantinos Fokianos
Publisher: CRC Press
ISBN: 9781482248050
Category :
Languages : en
Pages : 220

View

Book Description

Author: Yan Liu
Publisher: Springer Nature
ISBN: 9819908035
Category : Mathematics
Languages : en
Pages : 591

View

Book Description
This book compiles theoretical developments on statistical inference for time series and related models in honor of Masanobu Taniguchi's 70th birthday. It covers models such as long-range dependence models, nonlinear conditionally heteroscedastic time series, locally stationary processes, integer-valued time series, Lévy Processes, complex-valued time series, categorical time series, exclusive topic models, and copula models. Many cutting-edge methods such as empirical likelihood methods, quantile regression, portmanteau tests, rank-based inference, change-point detection, testing for the goodness-of-fit, higher-order asymptotic expansion, minimum contrast estimation, optimal transportation, and topological methods are proposed, considered, or applied to complex data based on the statistical inference for stochastic processes. The performances of these methods are illustrated by a variety of data analyses. This collection of original papers provides the reader with comprehensive and state-of-the-art theoretical works on time series and related models. It contains deep and profound treatments of the asymptotic theory of statistical inference. In addition, many specialized methodologies based on the asymptotic theory are presented in a simple way for a wide variety of statistical models. This Festschrift finds its core audiences in statistics, signal processing, and econometrics.

Author: A. Colin Cameron
Publisher: Cambridge University Press
ISBN: 1107717795
Category : Business & Economics
Languages : en
Pages : 597

View

Book Description
Students in both social and natural sciences often seek regression methods to explain the frequency of events, such as visits to a doctor, auto accidents, or new patents awarded. This book, now in its second edition, provides the most comprehensive and up-to-date account of models and methods to interpret such data. The authors combine theory and practice to make sophisticated methods of analysis accessible to researchers and practitioners working with widely different types of data and software in areas such as applied statistics, econometrics, marketing, operations research, actuarial studies, demography, biostatistics and quantitative social sciences. The new material includes new theoretical topics, an updated and expanded treatment of cross-section models, coverage of bootstrap-based and simulation-based inference, expanded treatment of time series, multivariate and panel data, expanded treatment of endogenous regressors, coverage of quantile count regression, and a new chapter on Bayesian methods.

Author: Adrian Colin Cameron
Publisher: Cambridge University Press
ISBN: 1107014166
Category : Business & Economics
Languages : en
Pages : 597

View

Book Description
This book provides the most comprehensive and up-to-date account of regression methods to explain the frequency of events.

Author: Richard A. Davis
Publisher: CRC Press
ISBN: 1466577746
Category : Mathematics
Languages : en
Pages : 484

View

Book Description
Model a Wide Range of Count Time Series Handbook of Discrete-Valued Time Series presents state-of-the-art methods for modeling time series of counts and incorporates frequentist and Bayesian approaches for discrete-valued spatio-temporal data and multivariate data. While the book focuses on time series of counts, some of the techniques discussed ca

Author: Ansgar Steland
Publisher: Springer Nature
ISBN: 3030286657
Category : Mathematics
Languages : en
Pages : 449

View

Book Description
This volume presents selected and peer-reviewed contributions from the 14th Workshop on Stochastic Models, Statistics and Their Applications, held in Dresden, Germany, on March 6-8, 2019. Addressing the needs of theoretical and applied researchers alike, the contributions provide an overview of the latest advances and trends in the areas of mathematical statistics and applied probability, and their applications to high-dimensional statistics, econometrics and time series analysis, statistics for stochastic processes, statistical machine learning, big data and data science, random matrix theory, quality control, change-point analysis and detection, finance, copulas, survival analysis and reliability, sequential experiments, empirical processes, and microsimulations. As the book demonstrates, stochastic models and related statistical procedures and algorithms are essential to more comprehensively understanding and solving present-day problems arising in e.g. the natural sciences, machine learning, data science, engineering, image analysis, genetics, econometrics and finance.

Author: Gintautas Dzemyda
Publisher: Springer Nature
ISBN: 3031244532
Category : Technology & Engineering
Languages : en
Pages : 260

View

Book Description
This book provides an overview of a wide range of relevant applications and reveals how to solve them. Many of the latest applications in finance, technology, education, medicine and other important and relevant fields are data-driven. The volumes of data are enormous. Specific methods need to be developed or adapted to solve a particular problem. It illustrates data science in applications. These applications have in common the discovery of knowledge in data and the use of this knowledge to make real decisions. The set of examples presented serves as a recipe book for their direct application to similar problems or as a guide for the development of new, more sophisticated approaches. The intended readership is data scientists looking for appropriate solutions to their problems. In addition, the examples provided serves as material for lectures at universities.

Author: Joseph M. Hilbe
Publisher: Cambridge University Press
ISBN: 1107028337
Category : Business & Economics
Languages : en
Pages : 301

View

Book Description
This book provides guidelines and fully worked examples of how to select, construct, interpret and evaluate the full range of count models.

Author:
Publisher: Elsevier
ISBN: 0444538631
Category : Mathematics
Languages : en
Pages : 777

View

Book Description
The field of statistics not only affects all areas of scientific activity, but also many other matters such as public policy. It is branching rapidly into so many different subjects that a series of handbooks is the only way of comprehensively presenting the various aspects of statistical methodology, applications, and recent developments.The Handbook of Statistics is a series of self-contained reference books. Each volume is devoted to a particular topic in statistics, with Volume 30 dealing with time series. The series is addressed to the entire community of statisticians and scientists in various disciplines who use statistical methodology in their work. At the same time, special emphasis is placed on applications-oriented techniques, with the applied statistician in mind as the primary audience. - Comprehensively presents the various aspects of statistical methodology - Discusses a wide variety of diverse applications and recent developments - Contributors are internationally renowened experts in their respective areas

Author: William H. Greene
Publisher: Cambridge University Press
ISBN: 1139485954
Category : Business & Economics
Languages : en
Pages : 383

View

Book Description
It is increasingly common for analysts to seek out the opinions of individuals and organizations using attitudinal scales such as degree of satisfaction or importance attached to an issue. Examples include levels of obesity, seriousness of a health condition, attitudes towards service levels, opinions on products, voting intentions, and the degree of clarity of contracts. Ordered choice models provide a relevant methodology for capturing the sources of influence that explain the choice made amongst a set of ordered alternatives. The methods have evolved to a level of sophistication that can allow for heterogeneity in the threshold parameters, in the explanatory variables (through random parameters), and in the decomposition of the residual variance. This book brings together contributions in ordered choice modeling from a number of disciplines, synthesizing developments over the last fifty years, and suggests useful extensions to account for the wide range of sources of influence on choice.