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An Introduction to MATLAB
  • An Introduction to MATLAB
  • Where do I start?
  • 1. Crashcourse
    • Intro to Crashcourse
    • Graphical User Interface
    • Essential commands
      • Matrix Input and Access
      • Matrix Algebra
      • Logical Operations
    • Best practices
    • Self-Assessment
    • Applied exercises
  • 2. MATLAB Programming
    • Intro to MATLAB Programming
    • Programming Fundamentals
    • Conditions
    • Loops
    • Custom Functions
    • Debugging
    • Applied Exercises
  • 3. Data, Graphics & Reporting
    • Intro to Data, Graphics & Reporting
    • Working with Datasets
    • Creating Graphs
    • Applied Exercises
  • 4. RNGs & Simulations
    • Intro to RNGs & Simulations
    • Random Number Generation
    • Monte-Carlo Simulations
    • Applied Exercises
  • 5. Numerical Methods
    • Intro to Numerical Methods
    • Numerical Optimization
    • Numerical Solvers
    • Applied Exercises
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  1. 4. RNGs & Simulations

Intro to RNGs & Simulations

In this chapter we will discuss how to create pseudo-random numbers in MATLAB and how to run simulations.

PreviousApplied ExercisesNextRandom Number Generation

Last updated 5 years ago

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We start by discussing the core statistical distributions available in MATLAB and how to generate pseudo-random numbers for simulations.

Then, we discuss good practices and examples on how to write effective Monte-Carlo simulations.

Random Number Generation
Monte-Carlo Simulations