Selected Papers of Hirotugu Akaike

Selected Papers of Hirotugu Akaike
Author: Emanuel Parzen
Publisher: Springer Science & Business Media
Total Pages: 432
Release: 2012-12-06
Genre: Mathematics
ISBN: 146121694X

The pioneering research of Hirotugu Akaike has an international reputation for profoundly affecting how data and time series are analyzed and modelled and is highly regarded by the statistical and technological communities of Japan and the world. His 1974 paper "A new look at the statistical model identification" (IEEE Trans Automatic Control, AC-19, 716-723) is one of the most frequently cited papers in the area of engineering, technology, and applied sciences (according to a 1981 Citation Classic of the Institute of Scientific Information). It introduced the broad scientific community to model identification using the methods of Akaike's criterion AIC. The AIC method is cited and applied in almost every area of physical and social science. The best way to learn about the seminal ideas of pioneering researchers is to read their original papers. This book reprints 29 papers of Akaike's more than 140 papers. This book of papers by Akaike is a tribute to his outstanding career and a service to provide students and researchers with access to Akaike's innovative and influential ideas and applications. To provide a commentary on the career of Akaike, the motivations of his ideas, and his many remarkable honors and prizes, this book reprints "A Conversation with Hirotugu Akaike" by David F. Findley and Emanuel Parzen, published in 1995 in the journal Statistical Science. This survey of Akaike's career provides each of us with a role model for how to have an impact on society by stimulating applied researchers to implement new statistical methods.

Model Selection and Inference

Model Selection and Inference
Author: Kenneth P. Burnham
Publisher: Springer Science & Business Media
Total Pages: 373
Release: 2013-11-11
Genre: Mathematics
ISBN: 1475729170

Statisticians and applied scientists must often select a model to fit empirical data. This book discusses the philosophy and strategy of selecting such a model using the information theory approach pioneered by Hirotugu Akaike. This approach focuses critical attention on a priori modeling and the selection of a good approximating model that best represents the inference supported by the data. The book includes practical applications in biology and environmental science.

Hypothesis Testing and Model Selection in the Social Sciences

Hypothesis Testing and Model Selection in the Social Sciences
Author: David L. Weakliem
Publisher: Guilford Publications
Total Pages: 217
Release: 2016-04-25
Genre: Social Science
ISBN: 1462525652

Examining the major approaches to hypothesis testing and model selection, this book blends statistical theory with recommendations for practice, illustrated with real-world social science examples. It systematically compares classical (frequentist) and Bayesian approaches, showing how they are applied, exploring ways to reconcile the differences between them, and evaluating key controversies and criticisms. The book also addresses the role of hypothesis testing in the evaluation of theories, the relationship between hypothesis tests and confidence intervals, and the role of prior knowledge in Bayesian estimation and Bayesian hypothesis testing. Two easily calculated alternatives to standard hypothesis tests are discussed in depth: the Akaike information criterion (AIC) and Bayesian information criterion (BIC). The companion website ([ital]www.guilford.com/weakliem-materials[/ital]) supplies data and syntax files for the book's examples.

Model Selection and Multimodel Inference

Model Selection and Multimodel Inference
Author: Kenneth P. Burnham
Publisher: Springer Science & Business Media
Total Pages: 512
Release: 2007-05-28
Genre: Mathematics
ISBN: 0387224564

A unique and comprehensive text on the philosophy of model-based data analysis and strategy for the analysis of empirical data. The book introduces information theoretic approaches and focuses critical attention on a priori modeling and the selection of a good approximating model that best represents the inference supported by the data. It contains several new approaches to estimating model selection uncertainty and incorporating selection uncertainty into estimates of precision. An array of examples is given to illustrate various technical issues. The text has been written for biologists and statisticians using models for making inferences from empirical data.

Measurement in Marketing

Measurement in Marketing
Author: Hans Baumgartner
Publisher: Emerald Group Publishing
Total Pages: 241
Release: 2022-09-12
Genre: Business & Economics
ISBN: 1800436300

Measurement in Marketing is built to provide a state-of-the-art discussion of current topics in measurement and deepen readers’ appreciation of the fundamental role of measurement in empirical research in marketing.

Water Systems Analysis, Design, and Planning

Water Systems Analysis, Design, and Planning
Author: Mohammad Karamouz
Publisher: CRC Press
Total Pages: 1100
Release: 2021-12-29
Genre: Science
ISBN: 1000487350

This book presents three distinct pillars for analysis, design, and planning: urban water cycle and variability as the state of water being; landscape architecture as the medium for built-by-design; and total systems as the planning approach. The increasing demand for water and urban and industrial expansions have caused myriad environmental, social, economic, and political predicaments. More frequent and severe floods and droughts have changed the resiliency and ability of water infrastructure systems to operate and provide services to the public. These concerns and issues have also changed the way we plan and manage our water resources. Focusing on urban challenges and contexts, the book provides foundational information regarding water science and engineering while also examining topics relating to urban stormwater, water supply, and wastewater infrastructures. It also addresses critical emerging issues such as simulation and economic modeling, flood resiliency, environmental visualization, satellite data applications, and digital data model (DEM) advancements. Features: Explores various theoretical, practical, and real-world applications of system analysis, design, and planning of urban water infrastructures Discusses hydrology, hydraulics, and basic laws of water flow movement through natural and constructed environments Describes a wide range of novel topics ranging from water assets, water economics, systems analysis, risk, reliability, and disaster management Examines the details of hydrologic and hydrodynamic modeling and simulation of conceptual and data-driven models Delineates flood resiliency, environmental visualization, pattern recognition, and machine learning attributes Explores a compilation of tools and emerging techniques that elevate the reader to a higher plateau in water and environmental systems management Water Systems Analysis, Design, and Planning: Urban Infrastructure serves as a useful resource for advanced undergraduate and graduate students taking courses in the areas of water resources and systems analysis, as well as practicing engineers and landscape professionals.

Age, Period and Cohort Effects

Age, Period and Cohort Effects
Author: Andrew Bell
Publisher: Routledge
Total Pages: 245
Release: 2020-11-05
Genre: Psychology
ISBN: 0429616279

Age, Period and Cohort Effects: Statistical Analysis and the Identification Problem gives a number of perspectives from top methodologists and applied researchers on the best ways to attempt to answer Age–Period–Cohort related questions about society. Age–Period–Cohort (APC) analysis is a fundamental topic for any quantitative social scientist studying individuals over time. At the same time, it is also one of the most misunderstood and underestimated topics in quantitative methods. As such, this book is key reference material for researchers wanting to know how to deal with APC issues appropriately in their statistical modelling. It deals with the identification problem caused by the co-linearity of the three variables, considers why some currently used methods are problematic and suggests ideas for what applied researchers interested in APC analysis should do. Whilst the perspectives are varied, the book provides a unified view of the subject in a reader-friendly way that will be accessible to social scientists with a moderate level of quantitative understanding, across the social and health sciences.