Any R implementation for dimension reduction using random projection?
<p>I have a large p (~20K) and small n (~500) problem. The first thing I was thinking is dimension reduction. After trying PCA, robust PCA, ICA, removing highly correlated features, I was thinking to use Random Projection. However, there is no simple R implementation of Random Projection.</p>

<p>I have found a few random projection R packages, like</p>

<ol>
<li>MCLUST: <a href="https://cran.r-project.org/web/packages/mclust/index.html" rel="nofollow noreferrer">https://cran.r-project.org/web/packages/mclust/index.html</a></li>
<li>RPEnsemble: <a href="https://cran.r-project.org/web/packages/RPEnsemble/index.html" rel="nofollow noreferrer">https://cran.r-project.org/web/packages/RPEnsemble/index.html</a></li>
</ol>

<p>But, it seems that they don't support random projection directly for dimension reduction. I have limited knowledge about random projection, but I found two functions in sklearn support this:</p>

<p>Gaussian random projection and Sparse random projection:
<a href="http://scikit-learn.org/stable/modules/random_projection.html" rel="nofollow noreferrer">http://scikit-learn.org/stable/modules/random_projection.html</a></p>

<p>And it has pretty simple function interface. </p>

<p>Is that possible to implement random projection easily in R? Or, taking advantage of existing tools to do dimension reduction with Random Projection in R?</p>