1.

Record Nr.

UNINA9910298478403321

Autore

Dayal Vikram

Titolo

An Introduction to R for Quantitative Economics [[electronic resource] ] : Graphing, Simulating and Computing / / by Vikram Dayal

Pubbl/distr/stampa

New Delhi : , : Springer India : , : Imprint : Springer, , 2015

ISBN

81-322-2340-3

Edizione

[1st ed. 2015.]

Descrizione fisica

1 online resource (117 p.)

Collana

SpringerBriefs in Economics, , 2191-5504

Disciplina

519.502855133

Soggetti

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

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Description based upon print version of record.

Nota di bibliografia

Includes bibliographical references at the end of each chapters.

Nota di contenuto

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.

Sommario/riassunto

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.