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R Object-oriented Programming

You're reading from   R Object-oriented Programming A practical guide to help you learn and understand the programming techniques necessary to exploit the full power of R

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Product type Paperback
Published in Oct 2014
Publisher
ISBN-13 9781783986682
Length 190 pages
Edition 1st Edition
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Author (1):
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Kelly Black Kelly Black
Author Profile Icon Kelly Black
Kelly Black
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Toc

Overview

The base R environment has options for approximating many of the properties associated with probability distributions. This is not a complete discussion, and a more complete list can be found within the R environment using the help(Distributions) command. In this chapter, we will discuss how R can be used to approximate distribution functions, how to approximate cumulative distribution functions, how to approximate inverse cumulative distribution functions, Random Number Generation (RNG), and sampling.

The commands used for the first set of topics have a common format, and each command has the form of a prefix and a suffix. The suffix specifies the distribution by name. For example, the norm suffix refers to the normal distribution. A list of the distributions available in the base R installation is given in Table 1. The prefix is one of the following:

  • d: This determines the value of the distribution function, for example, dnorm is the height of the normal's probability distribution...
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