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An Introduction to R for Quantitative Economics : Graphing, Simulating and Computing / by Vikram Dayal.
- Format:
- Book
- Author/Creator:
- Dayal, Vikram, Author.
- Series:
- SpringerBriefs in Economics, 2191-5504
- Language:
- English
- Subjects (All):
- Econometrics.
- Statistics.
- Computer simulation.
- Artificial intelligence.
- R (Computer program language).
- Statistics for Business, Management, Economics, Finance, Insurance.
- Simulation and Modeling.
- Statistics and Computing/Statistics Programs.
- Artificial Intelligence.
- Local Subjects:
- Econometrics.
- Statistics for Business, Management, Economics, Finance, Insurance.
- Simulation and Modeling.
- Statistics and Computing/Statistics Programs.
- Artificial Intelligence.
- Physical Description:
- 1 online resource (117 p.)
- Edition:
- 1st ed. 2015.
- Place of Publication:
- New Delhi : Springer India : Imprint: Springer, 2015.
- Language Note:
- English
- Summary:
- This book gives an introduction to R to build up graphing, simulating and computing skills to enable one to see theoretical and statistical models in economics in a unified way. The great advantage of R is that it is free, extremely flexible and extensible. The book addresses the specific needs of economists, and helps them move up the R learning curve. It covers some mathematical topics such as, graphing the Cobb-Douglas function, using R to study the Solow growth model, in addition to statistical topics, from drawing statistical graphs to doing linear and logistic regression. It uses data that can be downloaded from the internet, and which is also available in different R packages. With some treatment of basic econometrics, the book discusses quantitative economics broadly and simply, looking at models in the light of data. Students of economics or economists keen to learn how to use R would find this book very useful.
- Contents:
- Chapter 1. Introduction
- Chapter 2. R and RStudio
- Chapter 3. Getting data into R
- Chapter 4. Supply and demand
- Chapter 5. Functions
- Chapter 6. The Cobb-Douglas Function
- Chapter 7. Matrices
- Chapter 8. Statistical simulation
- Chapter 9. Anscombe's quartet: graphs can reveal
- Chapter 10. Carbon and forests: graphs and regression
- Chapter 11. Evaluating training
- Chapter 12. The Solow growth model
- Chapter 13. Simulating random walks and shing cycles
- Chapter 14. Basic time series.
- Notes:
- Description based upon print version of record.
- Includes bibliographical references at the end of each chapters.
- ISBN:
- 81-322-2340-3
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