summary.cellPcaCoDa

Provides a more detailed summary than <code>print.cellPcaCoDa</code>,
including individual and cumulative proportions of variance for all
eigenvalues as well as the contamination rate per variable.

print

Methods for analysis of compositional data including robust
methods (<doi:10.1007/978-3-319-96422-5>), imputation of missing values (<doi:10.1016/j.csda.2009.11.023>), methods to replace
rounded zeros (<doi:10.1080/02664763.2017.1410524>, <doi:10.1016/j.chemolab.2016.04.011>, <doi:10.1016/j.csda.2012.02.012>),
count zeros (<doi:10.1177/1471082X14535524>),
methods to deal with essential zeros (<doi:10.1080/02664763.2016.1182135>), (robust) outlier
detection for compositional data, (robust) principal component analysis for
compositional data, (robust) factor analysis for compositional data, (robust)
discriminant analysis for compositional data (Fisher rule), robust regression
with compositional predictors, functional data analysis (<doi:10.1016/j.csda.2015.07.007>) and p-splines (<doi:10.1016/j.csda.2015.07.007>),
contingency (<doi:10.1080/03610926.2013.824980>)
and compositional tables (<doi:10.1111/sjos.12326>, <doi:10.1111/sjos.12223>, <doi:10.1080/02664763.2013.856871>)
and (robust) Anderson-Darling normality tests for
compositional data as well as popular log-ratio transformations (addLR, cenLR,
isomLR, and their inverse transformations). In addition, visualisation and
diagnostic tools are implemented as well as high and low-level plot functions
for the ternary diagram.

Matthias Templ

robCompositions

Compositional Data Analysis

Karel Hron

Peter Filzmoser

Kamila Facevicova

Petra Kynclova

Jan Walach

Veronika Pintar

Jiajia Chen

Dominika Miksova

Bernhard Meindl

Alessandra Menafoglio

Alessia Di Blasi

Federico Pavone

Nikola Stefelova

Gianluca Zeni

Roman Wiederkehr

summary.cellPcaCoDa function

<dl><dt>object</dt>
<dd>object of class <code>"cellPcaCoDa"</code> as returned by
<code>cellPcaCoDa</code></dd>
<dt>...</dt>
<dd>additional arguments (currently ignored)</dd></dl>

Arguments

Author

Summary method for cellwise-robust compositional PCA — summary.cellPcaCoDa

<dl>

<dt>object</dt>
<dd>object of class <code>"cellPcaCoDa"</code> as returned by
<code>cellPcaCoDa</code></dd>


<dt>...</dt>
<dd>additional arguments (currently ignored)</dd>

</dl>

Summary method for cellwise-robust compositional PCA

summary.cellPcaCoDa: Summary method for cellwise-robust compositional PCA

Description

Usage

Value

Arguments

Author

See Also

Examples