negbinomial

Parameterized as <code>mu</code> (mean; poisson lambda) and <code>size</code> (a shape parameter),
so you can do <code>rnbinom(10, mu = 10, size = 1)</code>. Read more in the doc for <code>rnbinom</code>,

Flexible and informed regression with Multiple Change Points. '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 Lindeløv (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

Jonas Kristoffer Lindeløv

negbinomial function

<dl><dt>link</dt>
<dd>Link function (Character).</dd></dl>

Arguments

Negative binomial for mcp — negbinomial

<dl>

<dt>link</dt>
<dd>Link function (Character).</dd>

</dl>

negbinomial: Negative binomial for mcp

Description

Usage

Arguments