Missing Observations, Additive Outliers and Inverse Autocorrelation Function PDF Download

Author: Agustín Maravall
Publisher:
ISBN:
Category : Autocorrelation (Statistics)
Languages : en
Pages : 56

View

Book Description

Author: Daniel Peña
Publisher: John Wiley & Sons
ISBN: 1118031229
Category : Mathematics
Languages : en
Pages : 494

View

Book Description
New statistical methods and future directions of research in time series A Course in Time Series Analysis demonstrates how to build time series models for univariate and multivariate time series data. It brings together material previously available only in the professional literature and presents a unified view of the most advanced procedures available for time series model building. The authors begin with basic concepts in univariate time series, providing an up-to-date presentation of ARIMA models, including the Kalman filter, outlier analysis, automatic methods for building ARIMA models, and signal extraction. They then move on to advanced topics, focusing on heteroscedastic models, nonlinear time series models, Bayesian time series analysis, nonparametric time series analysis, and neural networks. Multivariate time series coverage includes presentations on vector ARMA models, cointegration, and multivariate linear systems. Special features include: Contributions from eleven of the worldâ??s leading figures in time series Shared balance between theory and application Exercise series sets Many real data examples Consistent style and clear, common notation in all contributions 60 helpful graphs and tables Requiring no previous knowledge of the subject, A Course in Time Series Analysis is an important reference and a highly useful resource for researchers and practitioners in statistics, economics, business, engineering, and environmental analysis. An Instructor's Manual presenting detailed solutions to all the problems in he book is available upon request from the Wiley editorial department.

Author: Massimiliano Marcellino
Publisher:
ISBN:
Category : Automatic data collection systems
Languages : en
Pages : 44

View

Book Description

Author: Yadolah Dodge
Publisher: Springer Science & Business Media
ISBN: 3662268116
Category : Business & Economics
Languages : en
Pages : 565

View

Book Description
The Role of the Computer in Statistics David Cox Nuffield College, Oxford OXIINF, U.K. A classification of statistical problems via their computational demands hinges on four components (I) the amount and complexity of the data, (il) the specificity of the objectives of the analysis, (iii) the broad aspects of the approach to analysis, (ill) the conceptual, mathematical and numerical analytic complexity of the methods. Computational requi rements may be limiting in (I) and (ill), either through the need for special programming effort, or because of the difficulties of initial data management or because of the load of detailed analysis. The implications of modern computational developments for statistical work can be illustrated in the context of the study of specific probabilistic models, the development of general statistical theory, the design of investigations and the analysis of empirical data. While simulation is usually likely to be the most sensible way of investigating specific complex stochastic models, computerized algebra has an obvious role in the more analyti cal work. It seems likely that statistics and applied probability have made insufficient use of developments in numerical analysis associated more with classical applied mathematics, in particular in the solution of large systems of ordinary and partial differential equations, integral equations and integra-differential equations and for the ¢raction of "useful" in formation from integral transforms. Increasing emphasis on models incorporating specific subject-matter considerations is one route to bridging the gap between statistical ana.

Author: Roberto Baragona
Publisher: Springer Science & Business Media
ISBN: 3642162185
Category : Computers
Languages : en
Pages : 283

View

Book Description
This proposed text appears to be a good introduction to evolutionary computation for use in applied statistics research. The authors draw from a vast base of knowledge about the current literature in both the design of evolutionary algorithms and statistical techniques. Modern statistical research is on the threshold of solving increasingly complex problems in high dimensions, and the generalization of its methodology to parameters whose estimators do not follow mathematically simple distributions is underway. Many of these challenges involve optimizing functions for which analytic solutions are infeasible. Evolutionary algorithms represent a powerful and easily understood means of approximating the optimum value in a variety of settings. The proposed text seeks to guide readers through the crucial issues of optimization problems in statistical settings and the implementation of tailored methods (including both stand-alone evolutionary algorithms and hybrid crosses of these procedures with standard statistical algorithms like Metropolis-Hastings) in a variety of applications. This book would serve as an excellent reference work for statistical researchers at an advanced graduate level or beyond, particularly those with a strong background in computer science.

Author: Greg Kaser
Publisher:
ISBN:
Category : Nuclear power plants
Languages : en
Pages : 108

View

Book Description

Author:
Publisher:
ISBN:
Category : Europe
Languages : en
Pages : 48

View

Book Description

Author: Nicos M. Christodoulakis
Publisher:
ISBN:
Category : Competition, Imperfect
Languages : en
Pages : 52

View

Book Description

Author: Johann-Matthias Schulenburg (Graf von der.)
Publisher:
ISBN:
Category : Deregulation
Languages : en
Pages : 40

View

Book Description

Author: John Micklewright
Publisher:
ISBN:
Category : Supplemental unemployment benefits
Languages : en
Pages : 28

View

Book Description