print.bootMSmix

<code>print</code> method for class <code>"bootMSmix"</code>.

Fit and analysis of finite Mixtures of Mallows models with Spearman Distance for full and partial rankings with arbitrary missing positions. Inference is conducted within the maximum likelihood framework via Expectation-Maximization algorithms. Estimation uncertainty is tackled via diverse versions of bootstrapping as well as via Hessian-based standard errors calculations. The most relevant reference of the methods is Crispino, Mollica, Astuti and Tardella (2023) <doi:10.1007/s11222-023-10266-8>.

Cristina Mollica

MSmix

Finite Mixtures of Mallows Models with Spearman Distance for
Full and Partial Rankings

Marta Crispino

Lucia Modugno

Luca Tardella

print.bootMSmix function

<dl><dt>x</dt>
<dd>An object of class <code>"bootMSmix"</code> returned by <code>bootstrapMSmix</code>.</dd>
<dt>...</dt>
<dd>Further arguments passed to or from other methods (not used).</dd></dl>

Arguments

Print of the bootstrap confidence intervals for mixtures of Mallows models with Spearman distance — print.bootMSmix

<dl>

<dt>x</dt>
<dd>An object of class <code>"bootMSmix"</code> returned by <code>bootstrapMSmix</code>.</dd>


<dt>...</dt>
<dd>Further arguments passed to or from other methods (not used).</dd>

</dl>

print.bootMSmix: Print of the bootstrap confidence intervals for mixtures of Mallows models with Spearman distance

Description

Usage

Arguments