Abstract
In this chapter, we provide a very concise introduction to R. Furthermore, we briefly introduce some statistical concepts: Testing linear restrictions in regression models, the method of maximum likelihood estimation, and methods of numerical optimization.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
Note that the default delimiter is a space; hence, the file is actually not a comma separated value (csv) file.
- 2.
We follow closely the exposition in Johnston and DiNardo, Econometric Methods, 4th edition, page 90–99.
- 3.
Note that log() in R computes the natural logarithm.
- 4.
Because optim() by default minimizes we define a negative likelihood.
- 5.
The Newton–Raphson algorithm is available in the maxLik package.
References
Fox J, Weisberg S (2011) An R companion to applied regression. Sage Publications, Thousand Oaks
Greene WH (2003) Econometric analysis, 5th edn. Pearson Education, New Jersey
Johnston J, DiNardo J (1997) Econometric methods, 4th edn. R. R. Donnelley & Sons
R Core Team (2013) R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria, URL http://www.R-project.org/
Venables BD William N; Ripley (2002) Modern applied statistics with S, 4th edn. Springer, New York
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Behr, A. (2015). Introduction. In: Production and Efficiency Analysis with R. Springer, Cham. https://doi.org/10.1007/978-3-319-20502-1_1
Download citation
DOI: https://doi.org/10.1007/978-3-319-20502-1_1
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-20501-4
Online ISBN: 978-3-319-20502-1
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)