fit_arima

Changepoint detection algorithms for R are widespread but have
different interfaces and reporting conventions.
This makes the comparative analysis of results difficult.
We solve this problem by providing a tidy, unified interface for several
different changepoint detection algorithms.
We also provide consistent numerical and graphical reporting leveraging
the 'broom' and 'ggplot2' packages.

Ben Baumer

tidychangepoint

A Tidy Framework for Changepoint Detection Analysis

Benjamin S. Baumer

Biviana Marcela Suárez Sierra

Arrigo Coen

Carlos A. Taimal

Xueheng Shi

fit_arima function

<dl><dt>x</dt>
<dd>A time series</dd>
<dt>tau</dt>
<dd>a set of indices representing a changepoint set</dd>
<dt>...</dt>
<dd>currently ignored</dd></dl>

Arguments

Fit an ARIMA model — fit_arima

<dl>

<dt>x</dt>
<dd>A time series</dd>


<dt>tau</dt>
<dd>a set of indices representing a changepoint set</dd>


<dt>...</dt>
<dd>currently ignored</dd>

</dl>

Fit an ARIMA model

fit_arima: Fit an ARIMA model

Description

Usage

Value

Arguments

Details

See Also

Examples