@article{1463695,
      recid = {1463695},
      author = {Shahandashti, Mohsen, and Abediniangerabi, Bahram, and  Zahed, Ehsan, and Kim, Sooin,},
      title = {Construction analytics : forecasting and investment  valuation /},
      pages = {1 online resource (viii, 186 pages)},
      abstract = {This text covers R program coding for the implementation  of two essential data analytics for practical construction  problems. The first part of this book explains time series  basics, models, and forecasting approaches in the context  of the construction industry, accompanied by practical  examples in construction. The second part describes the  concept of investment valuation for construction projects  and provides both deterministic and probabilistic  techniques to conduct investment valuation on construction  projects. R code scripts are provided in this book for  solving practical problems in the construction industry.  This book is also equipped with an R Package entitled  "cdar" to provide the necessary functions for performing  investment valuation. The book maximizes students'  understanding of the necessary theoretical background of  data analytics, and explains the implementation of data  analytics techniques to solve the actual problems in the  construction industry. Illustrates theoretical explanations  of construction analytics, hands-on practices, and R codes  for analytics techniques; Enables readers to investigate  the problems in the construction industry such as cost  overruns and investment timing; Reinforces concepts  presented with problems and solutions, datasets, and  programming codes.},
      url = {http://library.usi.edu/record/1463695},
      doi = {https://doi.org/10.1007/978-3-031-27292-9},
}