Statistical and Econometric Methods for Transportation Data Analysis Second Edition

Statistical and Econometric Methods for Transportation Data Analysis  Second Edition Author Simon P. Washington
ISBN-10 9781420082852
Release 2010-12-02
Pages 544
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The complexity, diversity, and random nature of transportation problems necessitates a broad analytical toolbox. Describing tools commonly used in the field, Statistical and Econometric Methods for Transportation Data Analysis, Second Edition provides an understanding of a broad range of analytical tools required to solve transportation problems. It includes a wide breadth of examples and case studies covering applications in various aspects of transportation planning, engineering, safety, and economics. After a solid refresher on statistical fundamentals, the book focuses on continuous dependent variable models and count and discrete dependent variable models. Along with an entirely new section on other statistical methods, this edition offers a wealth of new material. New to the Second Edition A subsection on Tobit and censored regressions An explicit treatment of frequency domain time series analysis, including Fourier and wavelets analysis methods New chapter that presents logistic regression commonly used to model binary outcomes New chapter on ordered probability models New chapters on random-parameter models and Bayesian statistical modeling New examples and data sets Each chapter clearly presents fundamental concepts and principles and includes numerous references for those seeking additional technical details and applications. To reinforce a practical understanding of the modeling techniques, the data sets used in the text are offered on the book’s CRC Press web page. PowerPoint and Word presentations for each chapter are also available for download.



Statistical and Econometric Methods for Transportation Data Analysis Second Edition

Statistical and Econometric Methods for Transportation Data Analysis  Second Edition Author Simon P. Washington
ISBN-10 9781420082869
Release 2010-12-02
Pages 544
Download Link Click Here

The complexity, diversity, and random nature of transportation problems necessitates a broad analytical toolbox. Describing tools commonly used in the field, Statistical and Econometric Methods for Transportation Data Analysis, Second Edition provides an understanding of a broad range of analytical tools required to solve transportation problems. It includes a wide breadth of examples and case studies covering applications in various aspects of transportation planning, engineering, safety, and economics. After a solid refresher on statistical fundamentals, the book focuses on continuous dependent variable models and count and discrete dependent variable models. Along with an entirely new section on other statistical methods, this edition offers a wealth of new material. New to the Second Edition A subsection on Tobit and censored regressions An explicit treatment of frequency domain time series analysis, including Fourier and wavelets analysis methods New chapter that presents logistic regression commonly used to model binary outcomes New chapter on ordered probability models New chapters on random-parameter models and Bayesian statistical modeling New examples and data sets Each chapter clearly presents fundamental concepts and principles and includes numerous references for those seeking additional technical details and applications. To reinforce a practical understanding of the modeling techniques, the data sets used in the text are offered on the book’s CRC Press web page. PowerPoint and Word presentations for each chapter are also available for download.



Statistical and Econometric Methods for Transportation Data Analysis

Statistical and Econometric Methods for Transportation Data Analysis Author Simon P. Washington
ISBN-10 0203497112
Release 2004-06-02
Pages 440
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As the field of transportation moves toward the "total quality management" paradigm, performance-based outcomes and quantitative measures have become increasingly important. Measuring performance in the field depends heavily on modeling trends and data, which in turn requires powerful, and flexible analytical tools. To date, however, transportation professionals have lacked a unified, rigorous guide to modeling the wide range of problems they encounter in the field. Statistical and Econometric Methods for Transportation Data describes the techniques most useful for modeling the many complex aspects of transportation, such as travel demand, safety, emissions, and the environment. Taking care not to overwhelm readers with statistical theory, the authors clearly and concisely present the relevant analytical methods in quantitative chapters built on transportation case studies. Mastering this material enables readers to: Formulate research hypotheses Identify appropriate statistical and econometric models Avoid common pitfalls and misapplications of statistical methods Interpret model results correctly Ideal as both a textbook and reference, this book makes three unique contributions to transportation practice and education. First, it presents a host of analytical techniques-both common and sophisticated-used to model transportation phenomena. Second, it provides a wealth of examples and case studies, and third, it specifically targets present and future transportation professionals. It builds the foundation they need not only to apply analytical models but also to understand and interpret results published elsewhere.



Modelling Transport

Modelling Transport Author Juan de Dios Ortúzar
ISBN-10 9781119993520
Release 2011-05-03
Pages 606
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Already the market leader in the field, Modelling Transport has become still more indispensible following a thorough and detailed update. Enhancements include two entirely new chapters on modelling for private sector projects and on activity-based modelling; a new section on dynamic assignment and micro-simulation; and sizeable updates to sections on disaggregate modelling and stated preference design and analysis. It also tackles topical issues such as valuation of externalities and the role of GPS in travel time surveys. Providing unrivalled depth and breadth of coverage, each topic is approached as a modelling exercise with discussion of the roles of theory, data, model specification, estimation, validation and application. The authors present the state of the art and its practical application in a pedagogic manner, easily understandable to both students and practitioners. Follows on from the highly successful third edition universally acknowledged as the leading text on transport modelling techniques and applications Includes two new chapters on modelling for private sector projects and activity based modeling, and numerous updates to existing chapters Incorporates treatment of recent issues and concerns like risk analysis and the dynamic interaction between land use and transport Provides comprehensive and rigorous information and guidance, enabling readers to make practical use of every available technique Relates the topics to new external factors and technologies such as global warming, valuation of externalities and global positioning systems (GPS).



Transportation Statistics and Microsimulation

Transportation Statistics and Microsimulation Author Clifford Spiegelman
ISBN-10 9781439894545
Release 2016-04-19
Pages 384
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By discussing statistical concepts in the context of transportation planning and operations, Transportation Statistics and Microsimulation provides the necessary background for making informed transportation-related decisions. It explains the why behind standard methods and uses real-world transportation examples and problems to illustrate key concepts. The Tools and Methods to Solve Transportation Problems Classroom-tested at Texas A&M University, the text covers the statistical techniques most frequently employed by transportation and pavement professionals. To familiarize readers with the underlying theory and equations, it contains problems that can be solved using statistical software. The authors encourage the use of SAS’s JMP package, which enables users to interactively explore and visualize data. Students can buy their own copy of JMP at a reduced price via a postcard in the book. Practical Examples Show How the Methods Are Used in Action Drawing on the authors’ extensive application of statistical techniques in transportation research and teaching, this textbook explicitly defines the underlying assumptions of the techniques and shows how they are used in practice. It presents terms from both a statistical and a transportation perspective, making conversations between transportation professionals and statisticians smoother and more productive.



The Art of Regression Modeling in Road Safety

The Art of Regression Modeling in Road Safety Author Ezra Hauer
ISBN-10 9783319125299
Release 2014-12-10
Pages 231
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This unique book explains how to fashion useful regression models from commonly available data to erect models essential for evidence-based road safety management and research. Composed from techniques and best practices presented over many years of lectures and workshops, The Art of Regression Modeling in Road Safety illustrates that fruitful modeling cannot be done without substantive knowledge about the modeled phenomenon. Class-tested in courses and workshops across North America, the book is ideal for professionals, researchers, university professors, and graduate students with an interest in, or responsibilities related to, road safety. This book also: · Presents for the first time a powerful analytical tool for road safety researchers and practitioners · Includes problems and solutions in each chapter as well as data and spreadsheets for running models and PowerPoint presentation slides · Features pedagogy well-suited for graduate courses and workshops including problems, solutions, and PowerPoint presentations · Equips readers to perform all analyses on a spreadsheet without requiring mastery of complex and costly software · Emphasizes understanding without esoteric mathematics · Makes assumptions visible and explains their role and consequences



Applied Choice Analysis

Applied Choice Analysis Author David A. Hensher
ISBN-10 0521844266
Release 2005-06-02
Pages 717
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In recent years there has been a growing interest in the development and application of quantitative statistical methods to study choices made by individuals. This primer provides an introduction to the main techniques of choice analysis and also includes detail on data collection and preparation, model estimation and interpretation and the design of choice experiments. A companion website provides practice data sets and software to apply modeling and data skills presented in the book. An invaluable resource to students and of value to anyone interested in choice analysis and modelling.



Impact Evaluation in Practice

Impact Evaluation in Practice Author Sebastian Martinez
ISBN-10 9780821385418
Release 2011
Pages 244
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This handbook provide a non-technical introduction to impact evaluations, including ?Why Evaluate? in Chapter 1, ?How to Evaluate? in Chapter 2 and ?How to Implement Impact Evaluations? in Chapter 3. These elements are the basic ?tools? needed in order to successfully carry out an impact evaluation.



Transportation Systems Planning

Transportation Systems Planning Author Konstadinos G. Goulias
ISBN-10 9781420042283
Release 2002-12-26
Pages 456
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Transportation engineering and transportation planning are two sides of the same coin aiming at the design of an efficient infrastructure and service to meet the growing needs for accessibility and mobility. Many well-designed transport systems that meet these needs are based on a solid understanding of human behavior. Since transportation systems are the backbone connecting the vital parts of a city, in-depth understanding of human nature is essential to the planning, design, and operational analysis of transportation systems. With contributions by transportation experts from around the world, Transportation Systems Planning: Methods and Applications compiles engineering data and methods for solving problems in the planning, design, construction, and operation of various transportation modes into one source. It is the first methodological transportation planning reference that illustrates analytical simulation methods that depict human behavior in a realistic way, and many of its chapters emphasize newly developed and previously unpublished simulation methods. The handbook demonstrates how urban and regional planning, geography, demography, economics, sociology, ecology, psychology, business, operations management, and engineering come together to help us plan for better futures that are human-centered. The text reviews projects from an initial problem statement to final policy action and associated decision-making and examines policies at all levels of government, from the city to the national levels. Unlike many other handbooks which are encyclopedic reviews, Transportation Systems Planning extends far beyond modeling in engineering and economics to present a truly transdisciplinary approach to transportation systems planning.



Python for Data Analysis

Python for Data Analysis Author Wes McKinney
ISBN-10 9781449319793
Release 2012-10-22
Pages 452
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Presents case studies and instructions on how to solve data analysis problems using Python.



An Introduction to Efficiency and Productivity Analysis

An Introduction to Efficiency and Productivity Analysis Author Timothy J. Coelli
ISBN-10 0792380622
Release 1997-11-30
Pages 276
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An Introduction to Efficiency and Productivity Analysis is designed as a primer for anyone seeking an authoritative introduction to efficiency and productivity analysis. It is a systematic treatment of four relatively new methodologies in Efficiency/Production Analysis: (a) Least-Squares Econometric Production Models, (b) Total Factor Productivity (TFP) Indices, (c) Data Envelopment Analysis (DEA), and (d) Stochastic Frontiers. Each method is discussed thoroughly. First, the basic elements of each method are discussed using models to illustrate the method's fundamentals, and, second, the discussion is expanded to treat the extensions and varieties of each method's uses. Finally, one or more case studies are provided as a full illustration of how each methodology can be used. In addition, all four methodologies will be linked in the book's presentation by examining the advantages and disadvantages of each method and the problems to which each method can be most suitably applied. The book offers the first unified text presentation of methods that will be of use to students, researchers and practitioners who work in the growing area of Efficiency/Productivity Analysis. The book also provides detailed advice on computer programs which can be used to calculate the various measures. This involves a number of presentations of computer instructions and output listings for the SHAZAM, TFPIP, DEAP and FRONTIER computer programs.



Statistics and Data Analysis for Financial Engineering

Statistics and Data Analysis for Financial Engineering Author David Ruppert
ISBN-10 9781493926145
Release 2015-04-21
Pages 719
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The new edition of this influential textbook, geared towards graduate or advanced undergraduate students, teaches the statistics necessary for financial engineering. In doing so, it illustrates concepts using financial markets and economic data, R Labs with real-data exercises, and graphical and analytic methods for modeling and diagnosing modeling errors. These methods are critical because financial engineers now have access to enormous quantities of data. To make use of this data, the powerful methods in this book for working with quantitative information, particularly about volatility and risks, are essential. Strengths of this fully-revised edition include major additions to the R code and the advanced topics covered. Individual chapters cover, among other topics, multivariate distributions, copulas, Bayesian computations, risk management, and cointegration. Suggested prerequisites are basic knowledge of statistics and probability, matrices and linear algebra, and calculus. There is an appendix on probability, statistics and linear algebra. Practicing financial engineers will also find this book of interest.



Modeling Count Data

Modeling Count Data Author Joseph M. Hilbe
ISBN-10 9781107028333
Release 2014-07-21
Pages 300
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"This entry-level text offers clear and concise guidelines on how to select, construct, interpret, and evaluate count data. Written for researchers with little or no background in advanced statistics, the book presents treatments of all major models using numerous tables, insets, and detailed modeling suggestions. It begins by demonstrating the fundamentals of linear regression and works up to an analysis of the Poisson and negative binomial models, and to the problem of overdispersion. Examples in Stata, R, and SAS code enable readers to adapt models for their own purposes, making the text an ideal resource for researchers working in public health, ecology, econometrics, transportation, and other related fields"--



Introduction to Spatial Econometrics

Introduction to Spatial Econometrics Author James LeSage
ISBN-10 1420064258
Release 2009-01-20
Pages 340
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Although interest in spatial regression models has surged in recent years, a comprehensive, up-to-date text on these approaches does not exist. Filling this void, Introduction to Spatial Econometrics presents a variety of regression methods used to analyze spatial data samples that violate the traditional assumption of independence between observations. It explores a wide range of alternative topics, including maximum likelihood and Bayesian estimation, various types of spatial regression specifications, and applied modeling situations involving different circumstances. Leaders in this field, the authors clarify the often-mystifying phenomenon of simultaneous spatial dependence. By presenting new methods, they help with the interpretation of spatial regression models, especially ones that include spatial lags of the dependent variable. The authors also examine the relationship between spatiotemporal processes and long-run equilibrium states that are characterized by simultaneous spatial dependence. MATLAB® toolboxes useful for spatial econometric estimation are available on the authors’ websites. This work covers spatial econometric modeling as well as numerous applied illustrations of the methods. It encompasses many recent advances in spatial econometric models—including some previously unpublished results.



Analysis of Financial Data

Analysis of Financial Data Author Gary Koop
ISBN-10 0470032294
Release 2006-02-22
Pages 250
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Analysis of Financial Data has been writing in one form or another for most of life. You can find so many inspiration from Analysis of Financial Data also informative, and entertaining. Click DOWNLOAD or Read Online button to get full Analysis of Financial Data book for free.



Spatial Analysis Methods of Road Traffic Collisions

Spatial Analysis Methods of Road Traffic Collisions Author Becky P. Y. Loo
ISBN-10 9781439874134
Release 2015-09-21
Pages 322
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Examine the Prevalence and Geography of Road Collisions Spatial Analysis Methods of Road Traffic Collisions centers on the geographical nature of road crashes, and uses spatial methods to provide a greater understanding of the patterns and processes that cause them. Written by internationally known experts in the field of transport geography, the book outlines the key issues in identifying hazardous road locations (HRLs), considers current approaches used for reducing and preventing road traffic collisions, and outlines a strategy for improved road safety. The book covers spatial accuracy, validation, and other statistical issues, as well as link-attribute and event-based approaches, cluster identification, and risk exposure. The book provides a brief summary of the evolution of road safety in the twentieth century, explores current road safety problems, and establishes road safety as a public health issue. The authors discuss risk and socioeconomic factors, lifestyle and behavior, and the impact of urban development. They consider road engineering, signage, vehicle design, the education of road users, and the enforcement of traffic safety measures. They also factor in the overall impact of road traffic collisions on transportation systems, economic systems, health systems, and society as a whole. Combines theoretical methodology with empirical data Bridges research and practice in road safety Includes case studies from around the world Spatial Analysis Methods of Road Traffic Collisions takes a look at spatial methods and their role in analyzing road traffic collisions to improve road safety. A great addition to transportation safety practice and research, this book serves as a reference for spatial analysis researchers and postgraduate students in traffic and transportation engineering, transport, and urban transport planning.



Introduction to Scientific Programming and Simulation Using R Second Edition

Introduction to Scientific Programming and Simulation Using R  Second Edition Author Owen Jones
ISBN-10 9781466570016
Release 2014-06-12
Pages 606
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Learn How to Program Stochastic Models Highly recommended, the best-selling first edition of Introduction to Scientific Programming and Simulation Using R was lauded as an excellent, easy-to-read introduction with extensive examples and exercises. This second edition continues to introduce scientific programming and stochastic modelling in a clear, practical, and thorough way. Readers learn programming by experimenting with the provided R code and data. The book’s four parts teach: Core knowledge of R and programming concepts How to think about mathematics from a numerical point of view, including the application of these concepts to root finding, numerical integration, and optimisation Essentials of probability, random variables, and expectation required to understand simulation Stochastic modelling and simulation, including random number generation and Monte Carlo integration In a new chapter on systems of ordinary differential equations (ODEs), the authors cover the Euler, midpoint, and fourth-order Runge-Kutta (RK4) schemes for solving systems of first-order ODEs. They compare the numerical efficiency of the different schemes experimentally and show how to improve the RK4 scheme by using an adaptive step size. Another new chapter focuses on both discrete- and continuous-time Markov chains. It describes transition and rate matrices, classification of states, limiting behaviour, Kolmogorov forward and backward equations, finite absorbing chains, and expected hitting times. It also presents methods for simulating discrete- and continuous-time chains as well as techniques for defining the state space, including lumping states and supplementary variables. Building readers’ statistical intuition, Introduction to Scientific Programming and Simulation Using R, Second Edition shows how to turn algorithms into code. It is designed for those who want to make tools, not just use them. The code and data are available for download from CRAN.