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Intro to R statistic programming
The document introduces R as an open-source environment for statistical computing and programming, highlighting its capabilities in data manipulation and graphical output. It covers installation instructions for R and RStudio, along with procedures for installing and using R packages, specifically focusing on the quantmod package for trading. Additional resources, packages, and literature for further learning in R are also provided.
Intro to R statistic programming
- 1. An Introduction toR for Traders Ram Venkat Dawn Analytics
- 2. R environment • Ris an open source environment for statistical computing • An Integrated environment for data manipulation, calculation and graphical output • R is also a dynamic and object-oriented programming language • Standard install consists of around 30 core packages that cover most common statistical and other tasks • CRAN contains over 4000 contributed packages and it is growing
- 3. R , RStudioinstallation • Both R and RStudio are available in Windows, Mac, unix and Linux • R installation instruction : http://cran.r- project.org/doc/manuals/R-admin.html • Rstudio is a free open source IDE for R, we will be using Rstudio for this tutorial • RStudio can be downloaded from http://rstudio.org/download/
- 4. R packages andsample datasets • Installing an R package: e.g >install.packages(“quantmod “) • “quantmod” is package for trading and we will be using this for this tutorial • Using quantmod to load some basic data • Using in-built data sets of R
- 5. R as anobject-oriented language • Everything is an Object in R • A brief look at an R program • Calling R programs in batch mode • R functions and packages http://www.r-bloggers.com/create-an-r-package- in-under-6-minutes/ • Calling R from other languages • R Programming Model • Parallel R
- 6. R Objects andclasses • Core Objects – Vector – List – Functions • Other Objects Matrix – Array – Data Frames – Factors
- 7. Data inputs andData Cleaning • Through package interfaces • From CSV • From Databases • Excel interface • Data Cleaning facilities
- 8. R Graphics • graphics,lattice and grid packages • graphics Package charts: – barplot,dot chart,histogram,density plots,strp charts, quantile plots, scatter plots, image plots, contour plots, interaction plots, sunflower plots • Lattice splits a chart into different panels or groups , making multiple plots on same page easy
- 9. Statistical computing • DataAnalysis : Summary, Correlation, principal Component Analysis, Factor Analysis • Time Series • Probablity Distributions • Statistical tests • Regression Models • Classification Models • Clustering
- 10. quantmod package • “Arapid prototyping environment, where quant traders can quickly and cleanly explore and build trading models. “ • Quantmod example on data handling • Quantmod example on charting • Quantmod example on modelling • For more : www.quantmod.com/examples/
- 11. Other packages ofinterest to Traders • R-sig-finance is your best bet to keep track of the packages: https://stat.ethz.ch/pipermail/r-sig-finance/ • Other packages mentioned frequently : Rmetrics(fportfolio),portfolio, Rglpk_solve_LP (portfolio optimization) • Broker-specific: Ibrokers (IB)
- 12. R Books andTutorials • Book - “R in a Nutshell” by Joseph Adler (O'Reilly) • cran-R “An introduction to R” http://cran.r-project.org/doc/manuals/R-intro.html • Quck-R site : http://www.statmethods.net/ gives a discount on the book “R in Action” from Manning • R and time-series: http://www.stat.pitt.edu/stoffer/tsa3/
- 13. Thank You For anyclarification, send e-mail to ram@dawnanalytics.com