ex_ar

See how this data was simulated
<a href="https://github.com/lindeloev/mcp/blob/master/data-raw/ex_ar.R">here</a>
using <code>fit$simulate()</code>, including which parameters were used. See an analysis
<a href="https://lindeloev.github.io/mcp/">here</a>.

datasets

Flexible and informed regression with Multiple Change Points (MCP). 'mcp' can infer change points in means, variances, autocorrelation structure, and any combination of these, as well as the parameters of the segments in between. All parameters are estimated with uncertainty and prediction intervals are supported - also near the change points. 'mcp' supports hypothesis testing via Savage-Dickey density ratio, posterior contrasts, and cross-validation. 'mcp' is described in Lindel<c3><b8>v (submitted) <doi:10.31219/osf.io/fzqxv> and generalizes the approach described in Carlin, Gelfand, & Smith (1992) <doi:10.2307/2347570> and Stephens (1994) <doi:10.2307/2986119>.

Jonas Kristoffer Lindel<c3><b8>v

Regression with Multiple Change Points

ex_ar function

A data frame with 300 rows and 2 variables:<dl class="dl-horizontal">
<dt>time</dt><dd>The x-axis.</dd>
<dt>price</dt><dd>The y-axis.</dd>
</dl>

Format

See how this data was simulated
<a href='https://github.com/lindeloev/mcp/blob/master/data-raw/ex_ar.R'>here</a>
using <code>fit$simulate()</code>, including which parameters were used. See an analysis
<a href='https://lindeloev.github.io/mcp/'>here</a>.

A change point in a time series — ex_ar

A data frame with 300 rows and 2 variables:<dl class='dl-horizontal'>
<dt>time</dt><dd>The x-axis.</dd>
<dt>price</dt><dd>The y-axis.</dd>
</dl>

ex_ar: A change point in a time series

Description

Usage

Arguments

Format