- Built-in Functions
- User-built functions
- Extensions

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

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 |

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.

Functions | Description |
---|---|

`aov()` |
Fits an ANOVA Model |

`lm()` |
Fits a linear model |

`glm()` |
Fits a general linear model |

`t.test()` |
Conducts a t-test |

Functions created by the user for analysis

Needs to be ran once to the R environment

Will be lost when R session is closed

`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

Create a function for

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

Create a function for

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

Create a function for

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

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):

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

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

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

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.