Learn how to apply your understanding of R—the language of big data—in the SAS environment at an advanced level.
Overview
Syllabus
Introduction
- Welcome
- The basics of IML
- Similarities to R
- Additional techniques
- Demo: Working in Interactive mode in SAS Studio
- Demo: Basic matrix operations by example
- Modules: Functions and subroutines
- Random number generation in IML
- Demo: Simple linear regression from scratch
- Common IML modules
- Demo: Navigating the SAS/IML documentation
- Creating modules
- Storage techniques
- Demo: Creating functions and subroutines
- Pulling a SAS dataset into an IML matrix
- Creating or editing a SAS dataset with an IML matrix
- Demo: Calling SAS datasets from IML
- Calling SAS procedures from IML
- Demo: Submitting SAS procedures
- Syntax for simulations
- Demo: The Monty Hall simulation
- Simulation techniques in general
- Demo: Sampling distribution method 1, entirely in IML
- Demo: Sampling distribution method 2, iteratively calling SAS procedures from IML
- Demo: Sampling distribution method 3, intelligently calling SAS procedures with the BY statement
- Calling R from SAS in general
- Readying your machine to call R
- Moving code, data, and results between SAS and R
- Demo: Working with R from IML
Taught by
Jordan Bakerman
