print.pPCA

Prints the output of the <code>pPCA</code>

Performs partial principal component analysis of a large sparse matrix.
The matrix may be stored as a list of matrices to be concatenated (implicitly) horizontally.
Useful application includes cases where the number of total nonzero entries exceed the capacity of
32 bit integers (e.g., with large Single Nucleotide Polymorphism data).

Srika Raja

pPCA

Partial Principal Component Analysis of Partitioned Large Sparse
Matrices

Somak Dutta

print.pPCA function

<dl><dt>x</dt>
<dd>An object of class <code>pPCA</code> that contains the results of a partial principal component analysis.</dd>
<dt>digits</dt>
<dd>The number of decimal places to use in printing results such as variance explained and PC scores. Defaults to 3.</dd>
<dt>...</dt>
<dd>Further arguments passed to <code>print</code> for additional control over the output.</dd></dl>

Arguments

Print the Output of Principal Component Analysis (pPCA) — print.pPCA

<dl>

<dt>x</dt>
<dd>An object of class <code>pPCA</code> that contains the results of a partial principal component analysis.</dd>


<dt>digits</dt>
<dd>The number of decimal places to use in printing results such as variance explained and PC scores. Defaults to 3.</dd>


<dt>...</dt>
<dd>Further arguments passed to <code>print</code> for additional control over the output.</dd>

</dl>

print.pPCA: Print the Output of Principal Component Analysis (pPCA)

Description

Usage

Value

Arguments