Название: Data Envelopment Analysis with R Автор: Farhad Hosseinzadeh Lotfi, Ali Ebrahimnejad, Mohsen Vaez-Ghasemi
Издательство: Springer
Год: 2019 (2020 Edition)
Страниц: 244
Язык: английский
Формат: pdf (true), djvu
Размер: 10.1 MB
This book introduces readers to the use of R codes for optimization problems. First, it provides the necessary background to understand data envelopment analysis (DEA), with a special emphasis on fuzzy DEA. It then describes DEA models, including fuzzy DEA models, and shows how to use them to solve optimization problems with R. Further, it discusses the main advantages of R in optimization problems, and provides R codes based on real-world data sets throughout. Offering a comprehensive review of DEA and fuzzy DEA models and the corresponding R codes, this practice-oriented reference guide is intended for masters and Ph.D. students in various disciplines, as well as practitioners and researchers.
The data envelopment analysis (DEA) technique is used to identify the strengths and weaknesses of a set of decision-maker units. In this technique for each decision-making unit based on the data analysis, relative efficiency, pattern coordinates, rankings, congestion in inputs, return on the scale, Malmquist productivity index, cost efficiency, and profit efficiency can be evaluated. For each decision-making unit (DMU) belonging to a set of observed units, it is necessary to solve an independent optimization problem in order to achieve the above objectives.
R is a mathematical and object-oriented programming language designed primarily for statistical computing and data mining. Although R is often used for statistical computations, it can also be used for matrix computations, which is similar to software such as Octave and MATLAB. The programming language R covers a wide range of optimization of linear and nonlinear models, integer and quadratic programming as well as classical statistical tests, time series analysis, classification and clustering, and has high graphical capabilities. In the R environment, C, C ++, and FORTRAN have the ability to connect and invoke the program while the expert users can directly change the R objects by using the C code. Among the features of R can be graphical facilities for data analysis and drawing diagrams, a simple and advanced programming language including conditional expressions, loops, recursive functions, and a strong set of computing operators, arrays and matrices, software packages for data mining and analysis, storage, retrieval and manipulation of data, a multi-purpose library for analytical operations, and data mining libraries. This software is free and open source. In this way, there is a special interest to this software among scholars. R codes for each model are provided.
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