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R Object-oriented Programming

R Object-oriented Programming

By : Black
4.4 (9)
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R Object-oriented Programming

R Object-oriented Programming

4.4 (9)
By: Black

Overview of this book

This book is designed for people with some experience in basic programming practices. It is also assumed that they have some basic experience using R and are familiar using the command line in an R environment. Our primary goal is to raise a beginner to a more advanced level to make him/her more comfortable creating programs and extending R to solve common problems.
Table of Contents (14 chapters)
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4
4. Calculating Probabilities and Random Numbers
12
A. Package Management
13
Index

Examples

We will now provide a brief example to demonstrate how to use the Simulation and MonteCarlo classes described in the previous sections. We focus on the discrete simulation class, but additional examples can be found in the code that accompanies this text. In this example, we assume that the definitions for the simulation and MonteCarlo classes are contained in two files, simulationS3.R and monteCarloS3.R.

The Monte-Carlo simulations can be created by first creating an object from the MontyCarlo class and setting the values of the parameters as follows:

> source('simulationS3.R')
> source('monteCarloS3.R')

> monty <- MonteCarlo()
> monty$setParams(100,1,
                1.0,2.0,
                1.2,-0.3,0.65,0.2,
                0.03,0.04)

Now that an object from the MonteCarlo class is defined, an object from the DiscreteSimulation class is created, and the simulation object is used to generate the results from 500 simulations:

> a <- DiscreteSimulation...

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