𝔖 Scriptorium
✦   LIBER   ✦

πŸ“

Data Envelopment Analysis with R

✍ Scribed by Farhad Hosseinzadeh Lotfi, Ali Ebrahimnejad, Mohsen Vaez-Ghasemi, Zohreh Moghaddas


Publisher
Springer
Year
2020
Tongue
English
Leaves
244
Category
Library

⬇  Acquire This Volume

No coin nor oath required. For personal study only.

✦ Table of Contents


Preface......Page 3
Contents......Page 6
1.1 Brief Review on DEA......Page 10
1.2 Basic Definitions......Page 13
1.3 Different Models of DEA......Page 15
1.4 Fuzzy Set Theory......Page 19
References......Page 24
2.1 Preliminaries of R......Page 27
2.2 Basic Definitions......Page 28
2.4 Attributes......Page 31
2.5.1 Vectors......Page 32
2.5.2 Matrixes......Page 34
2.5.3 Arrays......Page 38
2.5.4 Lists......Page 39
2.5.5 Data Frames......Page 40
2.7 Logical Operators......Page 41
2.8 Use R in Calculation......Page 42
2.9 Basic Mathematical Functions......Page 43
2.10 If Structure......Page 44
2.12 If Else Conditional......Page 45
2.13 For Function......Page 46
2.14 While Command......Page 47
2.16.1 Data Command......Page 48
2.16.2 Scan Command......Page 49
2.16.4 Read.delim Command......Page 50
2.16.5 Fread Command......Page 51
2.17.2 Sink Command......Page 52
2.19 Convert Objects......Page 53
2.20 Conclusion......Page 58
References......Page 59
3.1 Introduction......Page 61
3.2.1 Input-Oriented CCR Envelopment Model with R Code......Page 62
3.2.2 Input-Oriented CCR Multiplier Model with R Code......Page 64
3.2.3 Input-Oriented BCC Multiplier Model with R Code......Page 68
3.2.4 Input-Oriented BCC Envelopment Model with R Code......Page 71
3.3.1 Output-Oriented CCR Envelopment Model with R Code......Page 75
3.3.2 Output-Oriented CCR Multiplier Model with R Code......Page 77
3.3.3 Output-Oriented BCC Multiplier Model with R Code......Page 82
3.3.4 Output-Oriented BCC Envelopment Model with R Code......Page 84
3.4.1 Additive CCR Model with R Code......Page 87
3.4.2 Additive BCC Model with R Code......Page 89
3.5.1 R Code for Input-Oriented BCC Multiplier Model with Ξ΅......Page 94
3.5.2 R Code for Input-Oriented CCR Multiplier Model with Ξ΅......Page 97
3.6.1 Two-Phase Input-Oriented BCC Envelopment Model with R Code......Page 99
3.6.2 Two-Phase Input-Oriented CCR Envelopment Model with R Code......Page 102
References......Page 106
4.2 AP Models with R Codes......Page 107
4.2.1 Input-Oriented AP Envelopment Model with R Code......Page 108
4.2.2 Output-Oriented AP Enveloping Model......Page 110
4.2.3 Input-Oriented AP Multiplier Model......Page 112
4.2.4 Output-Oriented AP Multiplier Model......Page 114
4.3 MAJ Super-Efficiency Model with R Code......Page 116
4.4 Norm L1 Super-Efficiency Model with R Code......Page 119
4.5.1 Returns to Scaleβ€”CCR Envelopment Model with R Code......Page 122
4.5.2 Returns to Scaleβ€”DEA Multiplier Model with R Code......Page 126
4.6 Cost Efficiency Model with R Code......Page 130
4.7 Revenue Efficiency DEA Model with R Code......Page 132
4.8.1 Malmquist Productivity Indexβ€”CCR Multiplier Model with R Code......Page 135
4.8.2 Malmquist Productivity Indexβ€”CCR Envelopment Model with R Code......Page 139
4.9.1 First Model of SBM with R Code......Page 144
4.9.2 Second Model of SBM with R Code......Page 147
4.10 Series Network DEA Model with R Code......Page 149
4.11 Profit Efficiency DEA Model with R Code......Page 151
4.12.1 Input-Oriented Slack Based DEA Model with R Code......Page 155
4.12.2 Output-Oriented Slack Based DEA Model with R Code......Page 158
4.13 Congestion DEA Model with R Code......Page 160
4.14 Common Set of Weights DEA Model with R Code......Page 164
4.15 Directional Efficiency DEA Model with R Code......Page 166
References......Page 170
5.1 Introduction......Page 171
5.2 The \alpha–Level Approach......Page 173
5.2.1 Kao and Liu’s Approach......Page 174
5.2.2 Saati et al.’s Approach......Page 181
5.3.1 Guo and Tanaka’s Approach......Page 184
5.3.2 Leon et al.’s Approach......Page 188
5.3.3 Soleimani-damaneh et al.’s Approach......Page 196
5.4 The Possibility Approach......Page 198
5.5.1 Wang et al.’s Approach......Page 204
5.5.2 Bhardwaj et al.’s Approach......Page 215
5.5.3 Azar et al.’s Approach......Page 222
5.5.4 The MOLP Approach......Page 226
References......Page 243


πŸ“œ SIMILAR VOLUMES


Data Envelopment Analysis with R
✍ Farhad Hosseinzadeh Lotfi, Ali Ebrahimnejad, Mohsen Vaez-Ghasemi, Zohreh Moghadd πŸ“‚ Library πŸ“… 2020 πŸ› Springer International Publishing 🌐 English

<p><p>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

Data Envelopment Analysis with R
✍ Farhad Hosseinzadeh Lotfi; Ali Ebrahimnejad; Mohsen Vaez-Ghasemi; Zohreh Moghadd πŸ“‚ Library πŸ“… 2019 πŸ› Springer 🌐 English

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

Data Analysis with R
✍ Fischetti, Tony πŸ“‚ Library πŸ“… 2015 πŸ› Packt Publishing 🌐 English

Load, wrangle, and analyze your data using the world's most powerful statistical programming languageAbout This Book Load, manipulate and analyze data from different sources Gain a deeper understanding of fundamentals of applied statistics A practical guide to performing data analysis in practiceWho

Data Analysis with R
✍ Fischetti, Tony πŸ“‚ Library πŸ“… 2015 πŸ› Packt Publishing 🌐 English

Load, wrangle, and analyze your data using the world's most powerful statistical programming languageAbout This Book Load, manipulate and analyze data from different sources Gain a deeper understanding of fundamentals of applied statistics A practical guide to performing data analysis in practiceWho

Data Analysis with R
✍ Tony Fischetti πŸ“‚ Library πŸ“… 2016 πŸ› Packt Publishing 🌐 English

<h4>Key Features</h4><ul><li>Load, manipulate and analyze data from different sources</li><li>Gain a deeper understanding of fundamentals of applied statistics</li><li>A practical guide to performing data analysis in practice</li></ul><h4>Book Description</h4><p>Frequently the tool of choice for aca