Essays on Paired Data Models and Testing Heterogeneity
Author : Weiqiang Qian
Publisher :
Page : 230 pages
File Size : 23,92 MB
Release : 2008
Category : Econometrics
ISBN :
Author : Weiqiang Qian
Publisher :
Page : 230 pages
File Size : 23,92 MB
Release : 2008
Category : Econometrics
ISBN :
Author : Ning Zhang
Publisher :
Page : 510 pages
File Size : 38,84 MB
Release : 2005
Category :
ISBN :
Author : Christopher F. Parmeter
Publisher : Emerald Group Publishing
Page : 487 pages
File Size : 32,48 MB
Release : 2024-04-05
Category : Business & Economics
ISBN : 1837978735
It is the editor’s distinct privilege to gather this collection of papers that honors Subhal Kumbhakar’s many accomplishments, drawing further attention to the various areas of scholarship that he has touched.
Author : Shiv K. Saini
Publisher :
Page : 162 pages
File Size : 43,7 MB
Release : 2008
Category :
ISBN :
Author : Anne Boomsma
Publisher : Springer Science & Business Media
Page : 450 pages
File Size : 29,3 MB
Release : 2012-12-06
Category : Social Science
ISBN : 1461301696
This collection of papers provides an up to date treatment of item response theory, an important topic in educational testing.
Author : Alexander Chudik
Publisher : Emerald Group Publishing
Page : 316 pages
File Size : 44,90 MB
Release : 2022-01-18
Category : Business & Economics
ISBN : 180262063X
The collection of chapters in Volume 43 Part A of Advances in Econometrics serves as a tribute to one of the most innovative, influential, and productive econometricians of his generation, Professor M. Hashem Pesaran.
Author : Kalena Eliana Cortes
Publisher :
Page : 256 pages
File Size : 46,84 MB
Release : 2002
Category :
ISBN :
Author : Adam Sanoé Booij
Publisher : Rozenberg Publishers
Page : 174 pages
File Size : 13,30 MB
Release : 2009
Category :
ISBN : 9036101190
Author : H. Prakken
Publisher : IOS Press
Page : 498 pages
File Size : 18,15 MB
Release : 2020-09-25
Category : Computers
ISBN : 1643681079
The investigation of computational models of argument is a rich and fascinating interdisciplinary research field with two ultimate aims: the theoretical goal of understanding argumentation as a cognitive phenomenon by modeling it in computer programs, and the practical goal of supporting the development of computer-based systems able to engage in argumentation-related activities with human users or among themselves. The biennial International Conferences on Computational Models of Argument (COMMA) provide a dedicated forum for the presentation and discussion of the latest advancements in the field, and cover both basic research and innovative applications. This book presents the proceedings of COMMA 2020. Due to the Covid-19 pandemic, COMMA 2020 was held as an online event on the originally scheduled dates of 8 -11 September 2020, organised by the University of Perugia, Italy. The book includes 28 full papers and 13 short papers selected from a total of 78 submissions, the abstracts of 3 invited talks and 13 demonstration abstracts. The interdisciplinary nature of the field is reflected, and contributions cover both theory and practice. Theoretical contributions include new formal models, the study of formal or computational properties of models, designs for implemented systems and experimental research. Practical papers include applications to medicine, law and criminal investigation, chatbots and online product reviews. The argument-mining trend from previous COMMA’s is continued, while an emerging trend this year is the use of argumentation for explainable AI. The book provided an overview of the latest work on computational models of argument, and will be of interest to all those working in the field.
Author : Gilberto Rivera
Publisher : Springer Nature
Page : 597 pages
File Size : 25,24 MB
Release : 2023-10-20
Category : Computers
ISBN : 3031383257
In the age of transformative artificial intelligence (AI), which has the potential to revolutionize our lives, this book provides a comprehensive exploration of successful research and applications in AI and data analytics. Covering innovative approaches, advanced algorithms, and data analysis methodologies, this book addresses complex problems across topics such as machine learning, pattern recognition, data mining, optimization, and predictive modeling. With clear explanations, practical examples, and cutting-edge research, this book seeks to expand the understanding of a wide readership, including students, researchers, practitioners, and technology enthusiasts eager to explore these exciting fields. Featuring real-world applications in education, health care, climate modeling, cybersecurity, smart transportation, conversational systems, and material analysis, among others, this book highlights how these technologies can drive innovation and generate competitive advantages.