colSds

rowSds

Produces the same result as <code>apply(x, 1, sd)</code> or <code>apply(x, 2, sd)</code>
without coercing matrix to dense matrix. Values are not identical to
<code><a href="/link/sd()?package=proxyC&version=0.5.0" data-mini-rdoc="proxyC::sd()">sd()</a></code> because of the floating point precision issue in C++.

Computes proximity between rows or columns of large matrices efficiently in C++.
Functions are optimised for large sparse matrices using the Armadillo and Intel TBB libraries.
Among various built-in similarity/distance measures, computation of correlation,
cosine similarity, Dice coefficient and Euclidean distance is particularly fast.

Kohei Watanabe

proxyC

Computes Proximity in Large Sparse Matrices

Robrecht Cannoodt

colSds function

<dl><dt>x</dt>
<dd>a <a href="/link/base%3A%3Amatrix?package=proxyC&version=0.5.0" data-mini-rdoc="proxyC::base::matrix">base::matrix</a> or <a href="/link/Matrix%3A%3AMatrix?package=proxyC&version=0.5.0" data-mini-rdoc="proxyC::Matrix::Matrix">Matrix::Matrix</a> object.</dd></dl>

Arguments

Produces the same result as <code>apply(x, 1, sd)</code> or <code>apply(x, 2, sd)</code>
without coercing matrix to dense matrix. Values are not identical to
<code><a href='https://rdrr.io/r/stats/sd.html'>sd()</a></code> because of the floating point precision issue in C++.

Standard deviation of columns and rows of large matrices — colSds

<dl>

<dt>x</dt>
<dd>a <a href='https://rdrr.io/r/base/matrix.html'>base::matrix</a> or <a href='https://rdrr.io/pkg/Matrix/man/Matrix.html'>Matrix::Matrix</a> object.</dd>

</dl>

colSds: Standard deviation of columns and rows of large matrices

Description

Usage

Arguments

Examples