Advances in Shipping Data Analysis and Modeling


Book Description

Shipping flows – maritime ‘footprints’ – remain underexplored in the existing literature despite the crucial importance of freight transport for global trade and economic development. Additionally, decision-makers lack a comprehensive view on how shipping flows can be measured, analyzed, and mapped in order to support their policies and strategies. This interdisciplinary volume, drawing on an international cast-list of experts, explores a number of crucial issues in shipping data estimation, construction, collection, mining, analysis, visualization, and mapping. Advances in Shipping Data Analysis and Modeling delivers several key messages. First, that in a world of just-in-time delivery and rapid freight transit, it is important to bear in mind the long-term roots of current trends as well as foreseeable future developments because shipping patterns exhibit recurrent, if not cyclical and path-dependent, dynamics. Second, shipping flows are currently often understood at the micro-level of intra-urban logistics delivery and at the national level using commodity flow analyses, but this volume emphasizes the need to expand the scale of analysis by offering new evidence on the changing distribution of global and international shipping flows, based on actual data. Third, that this multidisciplinary approach to shipping flows can shed important light on crucial issues that go beyond shipping itself including climate change, urban development, technological change, commodity specialization, digital humanities, navigation patterns, international trade, and regional growth. Edited by experts in their field, this volume is of upmost importance to those who study industrial economics, shipping industries and economic and transport geography.




Applied Modeling Techniques and Data Analysis 1


Book Description

BIG DATA, ARTIFICIAL INTELLIGENCE AND DATA ANALYSIS SET Coordinated by Jacques Janssen Data analysis is a scientific field that continues to grow enormously, most notably over the last few decades, following rapid growth within the tech industry, as well as the wide applicability of computational techniques alongside new advances in analytic tools. Modeling enables data analysts to identify relationships, make predictions, and to understand, interpret and visualize the extracted information more strategically. This book includes the most recent advances on this topic, meeting increasing demand from wide circles of the scientific community. Applied Modeling Techniques and Data Analysis 1 is a collective work by a number of leading scientists, analysts, engineers, mathematicians and statisticians, working on the front end of data analysis and modeling applications. The chapters cover a cross section of current concerns and research interests in the above scientific areas. The collected material is divided into appropriate sections to provide the reader with both theoretical and applied information on data analysis methods, models and techniques, along with appropriate applications.




Advanced Data Analysis and Modelling in Chemical Engineering


Book Description

Advanced Data Analysis and Modeling in Chemical Engineering provides the mathematical foundations of different areas of chemical engineering and describes typical applications. The book presents the key areas of chemical engineering, their mathematical foundations, and corresponding modeling techniques. Modern industrial production is based on solid scientific methods, many of which are part of chemical engineering. To produce new substances or materials, engineers must devise special reactors and procedures, while also observing stringent safety requirements and striving to optimize the efficiency jointly in economic and ecological terms. In chemical engineering, mathematical methods are considered to be driving forces of many innovations in material design and process development. - Presents the main mathematical problems and models of chemical engineering and provides the reader with contemporary methods and tools to solve them - Summarizes in a clear and straightforward way, the contemporary trends in the interaction between mathematics and chemical engineering vital to chemical engineers in their daily work - Includes classical analytical methods, computational methods, and methods of symbolic computation - Covers the latest cutting edge computational methods, like symbolic computational methods




Modeling and Data Analysis: An Introduction with Environmental Applications


Book Description

Can we coexist with the other life forms that have evolved on this planet? Are there realistic alternatives to fossil fuels that would sustainably provide for human society's energy needs and have fewer harmful effects? How do we deal with threats such as emergent diseases? Mathematical models—equations of various sorts capturing relationships between variables involved in a complex situation—are fundamental for understanding the potential consequences of choices we make. Extracting insights from the vast amounts of data we are able to collect requires analysis methods and statistical reasoning. This book on elementary topics in mathematical modeling and data analysis is intended for an undergraduate “liberal arts mathematics”-type course but with a specific focus on environmental applications. It is suitable for introductory courses with no prerequisites beyond high school mathematics. A great variety of exercises extends the discussions of the main text to new situations and/or introduces new real-world examples. Every chapter ends with a section of problems, as well as with an extended chapter project which often involves substantial computing work either in spreadsheet software or in the R statistical package.




Statistical and Econometric Methods for Transportation Data Analysis


Book Description

The book's website (with databases and other support materials) can be accessed here. Praise for the Second Edition: The second edition introduces an especially broad set of statistical methods ... As a lecturer in both transportation and marketing research, I find this book an excellent textbook for advanced undergraduate, Master’s and Ph.D. students, covering topics from simple descriptive statistics to complex Bayesian models. ... It is one of the few books that cover an extensive set of statistical methods needed for data analysis in transportation. The book offers a wealth of examples from the transportation field. —The American Statistician Statistical and Econometric Methods for Transportation Data Analysis, Third Edition offers an expansion over the first and second editions in response to the recent methodological advancements in the fields of econometrics and statistics and to provide an increasing range of examples and corresponding data sets. It describes and illustrates some of the statistical and econometric tools commonly used in transportation data analysis. It provides a wide breadth of examples and case studies, covering applications in various aspects of transportation planning, engineering, safety, and economics. Ample analytical rigor is provided in each chapter so that fundamental concepts and principles are clear and numerous references are provided for those seeking additional technical details and applications. New to the Third Edition Updated references and improved examples throughout. New sections on random parameters linear regression and ordered probability models including the hierarchical ordered probit model. A new section on random parameters models with heterogeneity in the means and variances of parameter estimates. Multiple new sections on correlated random parameters and correlated grouped random parameters in probit, logit and hazard-based models. A new section discussing the practical aspects of random parameters model estimation. A new chapter on Latent Class Models. A new chapter on Bivariate and Multivariate Dependent Variable Models. Statistical and Econometric Methods for Transportation Data Analysis, Third Edition can serve as a textbook for advanced undergraduate, Masters, and Ph.D. students in transportation-related disciplines including engineering, economics, urban and regional planning, and sociology. The book also serves as a technical reference for researchers and practitioners wishing to examine and understand a broad range of statistical and econometric tools required to study transportation problems.




Advances in Shipping Data Analysis and Modeling


Book Description

Shipping flows - maritime 'footprints' - remain underexplored in the existing literature despite the crucial importance of freight transport for global trade and economic development. Additionally, decision-makers lack a comprehensive view on how shipping flows can be measured, analyzed, and mapped in order to support their policies and strategies. This interdisciplinary volume, drawing on an international cast-list of experts, explores a number of crucial issues in shipping data estimation, construction, collection, mining, analysis, visualization, and mapping. Advances in Shipping Data Analysis and Modeling delivers several key messages. First, that in a world of just-in-time delivery and rapid freight transit, it is important to bear in mind the long-term roots of current trends as well as foreseeable future developments because shipping patterns exhibit recurrent, if not cyclical and path-dependent, dynamics. Second, shipping flows are currently often understood at the micro-level of intra-urban logistics delivery and at the national level using commodity flow analyses, but this volume emphasizes the need to expand the scale of analysis by offering new evidence on the changing distribution of global and international shipping flows, based on actual data. Third, that this multidisciplinary approach to shipping flows can shed important light on crucial issues that go beyond shipping itself including climate change, urban development, technological change, commodity specialization, digital humanities, navigation patterns, international trade, and regional growth. Edited by experts in their field, this volume is of upmost importance to those who study industrial economics, shipping industries and economic and transport geography.




Advanced Time Series Data Analysis


Book Description

Introduces the latest developments in forecasting in advanced quantitative data analysis This book presents advanced univariate multiple regressions, which can directly be used to forecast their dependent variables, evaluate their in-sample forecast values, and compute forecast values beyond the sample period. Various alternative multiple regressions models are presented based on a single time series, bivariate, and triple time-series, which are developed by taking into account specific growth patterns of each dependent variables, starting with the simplest model up to the most advanced model. Graphs of the observed scores and the forecast evaluation of each of the models are offered to show the worst and the best forecast models among each set of the models of a specific independent variable. Advanced Time Series Data Analysis: Forecasting Using EViews provides readers with a number of modern, advanced forecast models not featured in any other book. They include various interaction models, models with alternative trends (including the models with heterogeneous trends), and complete heterogeneous models for monthly time series, quarterly time series, and annually time series. Each of the models can be applied by all quantitative researchers. Presents models that are all classroom tested Contains real-life data samples Contains over 350 equation specifications of various time series models Contains over 200 illustrative examples with special notes and comments Applicable for time series data of all quantitative studies Advanced Time Series Data Analysis: Forecasting Using EViews will appeal to researchers and practitioners in forecasting models, as well as those studying quantitative data analysis. It is suitable for those wishing to obtain a better knowledge and understanding on forecasting, specifically the uncertainty of forecast values.




Advances in Computational Algorithms and Data Analysis


Book Description

Advances in Computational Algorithms and Data Analysis offers state of the art tremendous advances in computational algorithms and data analysis. The selected articles are representative in these subjects sitting on the top-end-high technologies. The volume serves as an excellent reference work for researchers and graduate students working on computational algorithms and data analysis.




The SAGE Sourcebook of Advanced Data Analysis Methods for Communication Research


Book Description

A must-have volume for every communication researcher's library, The SAGE Sourcebook of Advanced Data Analysis Methods for Communication Research provides an introductory treatment of various advanced statistical methods applied to research in the field of communication. Written by authors who use these methods in their own research, each chapter gives a non-technical overview of what the method is and how it can be used to answer communication-related questions or aide the researcher dealing with difficult data problems. Students and faculty interested in diving into a new statistical topic—such as latent growth modeling, multilevel modeling, propensity scoring, or time series analysis—will find each chapter an excellent springboard for acquiring the background needed to jump into more advanced, technical readings.




Data Analysis


Book Description

Noted for its model-comparison approach and unified framework based on the general linear model (GLM), this classic text provides readers with a greater understanding of a variety of statistical procedures including analysis of variance (ANOVA) and regression.