Statistical and econometric methods for transportation data analysis
著者
書誌事項
Statistical and econometric methods for transportation data analysis
Chapman & Hall/CRC, c2003
大学図書館所蔵 全19件
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  福島
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  石川
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  長野
  岐阜
  静岡
  愛知
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  滋賀
  京都
  大阪
  兵庫
  奈良
  和歌山
  鳥取
  島根
  岡山
  広島
  山口
  徳島
  香川
  愛媛
  高知
  福岡
  佐賀
  長崎
  熊本
  大分
  宮崎
  鹿児島
  沖縄
  韓国
  中国
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  イギリス
  ドイツ
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注記
Includes bibliographical references (p. 395-412) and index
内容説明・目次
内容説明
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.
目次
FUNDAMENTALS
Statistical Inference I: Descriptive Statistics
Statistical Inference II: Interval Estimation, Hypothesis Testing, and Population Comparisons
CONTINUOUS DEPENDENT VARIABLE MODELS
Linear Regression
Violation of Regression Assumptions
Simultaneous Equations Models
Panel Data Analysis
Time Series Analysis
Latent Variable Models
Duration Models
COUNT AND DISCRETE DEPENDENT VARIABLE MODELS
Count Data Models
Discrete Outcome Models
Discrete/Continuous Models
APPENDIXES
Statistical Fundamentals
Glossary of Terms
Tables of Distributions: t, Z, chi-Square, F, Durbin-Watson
Variable Transformations
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