SummaryOutliers | R Documentation |

Use the command "tso" of the R package "tsoutliers" to identify outliers for each individual time series.

SummaryOutliers( x, type = c("LS", "AO", "TC"), tsmethod = "arima", args.tsmethod = list(order = c(5, 0, 0)) )

`x` |
T by k data matrix: T data points in rows with each row being data at a given time point, and k time series in columns. |

`type` |
A character vector indicating the type of outlier to be considered by the detection procedure. See 'types' in tso function. |

`tsmethod` |
The framework for time series modeling. Default is "arima". See 'tsmethod' in tso function. |

`args.tsmethod` |
An optional list containing arguments to be passed to the function invoking the method selected in tsmethod. See 'args.tsmethod' in tso function. Default value is c(5,0,0). |

A list containing:

Otable - Summary of various types of outliers detected.

x.cleaned - Outlier-adjusted data.

xadja - T-dimensional vector containing the number of time series that have outlier at a given time point.

data(TaiwanAirBox032017) output <- SummaryOutliers(TaiwanAirBox032017[1:50,1:3])

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.