penguins

The data set contains five measurements made on 342 penguins which are classified into three species.

datasets

Parsimonious Ultrametric Gaussian Mixture Models via grouped coordinate ascent (equivalent to EM) algorithm characterized by the inspection of hierarchical relationships among variables via parsimonious extended ultrametric covariance structures. The methodologies are described in Cavicchia, Vichi, Zaccaria (2024) <doi:10.1007/s11222-024-10405-9>, (2022) <doi:10.1007/s11634-021-00488-x> and (2020) <doi:10.1007/s11634-020-00400-z>.

Giorgia Zaccaria

PUGMM

Parsimonious Ultrametric Gaussian Mixture Models

Carlo Cavicchia

Lorenzo Balzotti

Alexa A. Sochaniwsky

Paul D. McNicholas

penguins function

A data frame with 342 observations and 5 variables, which are described as follows.<dl>
<dt>species</dt>
<dd>Penguin species (Chinstrap, Adélie, or Gentoo)</dd><dt>culmen_length_mm</dt>
<dd>Culmen length (mm)</dd><dt>culmen_depth_mm</dt>
<dd>Culmen depth (mm)</dd><dt>flipper_length_mm</dt>
<dd>Flipper length (mm)</dd><dt>body_mass_g</dt>
<dd>Body mass (g)</dd>
</dl>

Format

Penguins — penguins

A data frame with 342 observations and 5 variables, which are described as follows.<dl>
<dt>species</dt>
<dd>Penguin species (Chinstrap, Adélie, or Gentoo)</dd>

<dt>culmen_length_mm</dt>
<dd>Culmen length (mm)</dd>

<dt>culmen_depth_mm</dt>
<dd>Culmen depth (mm)</dd>

<dt>flipper_length_mm</dt>
<dd>Flipper length (mm)</dd>

<dt>body_mass_g</dt>
<dd>Body mass (g)</dd>


</dl>

penguins: Penguins

Description

Usage

Arguments

Format

Details

References

Examples