Functions

Learning Objectives

Built-in Functions
User-built functions
Extensions

Built-in Functions

There are several available functions in R to conduct specific statistical methods or tasks

Help Documentation

Section	Description
Description	Provides a brief introduction of the function
Usage	Provides potential usage of the function
Arguments	Arguments that the function can take
Details	An in depth description of the function
Value	Provides information of the output produced by the function
Notes	Any need to know information about the function
Authors	Developers of the function
References	References to the model and function
See Also	Provide information of supporting functions
Examples	Examples of the function

Generic Functions

Several R objects have a known class attached to it. A specialized object designed to be read by generic functions, such as summary() and plot().

For example, the summary() is a generic for several types of functions: summary.aov(), summary.lm(), summary.glm(), and many more.

Commonly-used Function

Functions	Description
`aov()`	Fits an ANOVA Model
`lm()`	Fits a linear model
`glm()`	Fits a general linear model
`t.test()`	Conducts a t-test

User-built functions

Functions created by the user for analysis
Needs to be ran once to the R environment
Will be lost when R session is closed

Anatomy

name_of_function <- function(data_1, data_2 = NULL, 
                             argument_1, argument_2 = TRUE, argument_3 = NULL,
                             ...){
  # Conduct Task
  # Conduct Task
  output_object <- Tasks
  return(output_object)
}

function: used to construct the function
data1: first data argument that needs to supplied
data2: second data argument that does not need to be supplied
argument1: first argument must be supplied to alter function
argument2: second argument to alter function, set to TRUE
argument3: third argument that does not need to be supplied
…: additional arguments supplied to other functions

Example

Create a function for

\[ y = \ln(x^2) \]

Example

Create a function for

\[ f(x) = \left\{\begin{array}{cc} x^3 & x<0\\ x^2 + 5 & \mathrm{otherwise} \end{array} \right. \]

Example

Create a function for

\[ f(x,y) = \left\{\begin{array}{cc} x^3 e^y & x<0\ \\ x^2 + 5 + \ln(y) & \mathrm{otherwise} \end{array} \right. \]

Example

Create the function that allows your to compute the z-score of a specific value x using the sampling distribution from a set of data (y vector):

\[ z = \frac{x-\bar y}{\sqrt{s^2_{y}/n_y}} \]

Extensions

R Packages

R Packages are used to utilize functions created from the community.

Installation

install.packages("tidyverse")

Loading

library(tidyverse)

Reticulate

Reticulate is an R package that allows you utilized python within R.

Rcpp

Rcpp is an R package that allows you to call C++ programs in R.

This is an extremely advanced topic. Only do this if you need real speed and efficiency.