This is a wrapper for the <code>RGCCA::rgcca</code> function for computing IFA.

Functions and datasets to support Smilde, Næs and Liland (2021, ISBN: 978-1-119-60096-1)
"Multiblock Data Fusion in Statistics and Machine Learning - Applications in the Natural and Life Sciences".
This implements and imports a large collection of methods for multiblock data analysis with common interfaces, result- and plotting
functions, several real data sets and six vignettes covering a range different applications.

Kristian Hovde Liland

multiblock

Multiblock Data Fusion in Statistics and Machine Learning

Solve Sæbø

Stefan Schrunner

ifa function

<dl><dt>X</dt>
<dd><code>list</code> of input data blocks.</dd>
<dt>ncomp</dt>
<dd><code>integer</code> number of principal components to return.</dd>
<dt>scale</dt>
<dd><code>logical</code> indicating if variables should be standardised (default=FALSE).</dd>
<dt>verbose</dt>
<dd><code>logical</code> indicating if intermediate results should be printed.</dd>
<dt>...</dt>
<dd>additional arguments to <code>RGCCA::rgcca</code>.</dd></dl>

Arguments

Inter-battery Factor Analysis - IFA — ifa

<dl>

<dt>X</dt>
<dd><code>list</code> of input data blocks.</dd>


<dt>ncomp</dt>
<dd><code>integer</code> number of principal components to return.</dd>


<dt>scale</dt>
<dd><code>logical</code> indicating if variables should be standardised (default=FALSE).</dd>


<dt>verbose</dt>
<dd><code>logical</code> indicating if intermediate results should be printed.</dd>


<dt>...</dt>
<dd>additional arguments to <code>RGCCA::rgcca</code>.</dd>

</dl>

ifa: Inter-battery Factor Analysis - IFA

Description

Usage

Value

Arguments

Details

References

See Also

Examples