print.cellPcaCoDa

Prints a concise summary of a <code>cellPcaCoDa</code> object including the
number of retained components, convergence status, the number and
percentage of flagged cells, and the cumulative explained variability.

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

print.cellPcaCoDa function

<dl><dt>x</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

Print method for cellwise-robust compositional PCA — print.cellPcaCoDa

<dl>

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


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

</dl>

Print method for cellwise-robust compositional PCA

print.cellPcaCoDa: Print method for cellwise-robust compositional PCA

Description

Usage

Value

Arguments

Author

See Also

Examples