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Commit a4d11521 authored by Armin Rauschenberger's avatar Armin Rauschenberger
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automation

parent 453d40f8
Package: joinet
Version: 0.0.1
Title: Multivariate Regression
Description: Implements high-dimensional multivariate regression by stacking (Rauschenberger et al. 2019).
Description: Implements high-dimensional multivariate regression by stacked generalisation (Wolpert 1992 <doi:10.1016/S0893-6080(05)80023-1>). For positively correlated outcomes, a single multivariate regression is typically more predictive than multiple univariate regressions. Includes functions for model fitting, extracting coefficients, outcome prediction, and performance measurement.
Depends: R (>= 3.0.0)
Imports: glmnet, palasso, cornet
Suggests: knitr, testthat, MASS
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## Scope
Stacked Elastic Net Regression (extending [glmnet](https://CRAN.R-project.org/package=glmnet)).
Multivariate Elastic Net Regression (extending [glmnet](https://CRAN.R-project.org/package=glmnet)).
## Installation
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......@@ -10,7 +10,7 @@ Status](https://codecov.io/github/rauschenberger/joinet/coverage.svg?branch=mast
## Scope
Stacked Elastic Net Regression (extending
Multivariate Elastic Net Regression (extending
[glmnet](https://CRAN.R-project.org/package=glmnet)).
## Installation
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<script src="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.3.7/js/bootstrap.min.js" integrity="sha256-U5ZEeKfGNOja007MMD3YBI0A3OSZOQbeG6z2f2Y0hu8=" crossorigin="anonymous"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/4.7.0/css/font-awesome.min.css" integrity="sha256-eZrrJcwDc/3uDhsdt61sL2oOBY362qM3lon1gyExkL0=" crossorigin="anonymous">
<!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.4/clipboard.min.js" integrity="sha256-FiZwavyI2V6+EXO1U+xzLG3IKldpiTFf3153ea9zikQ=" crossorigin="anonymous"></script><!-- sticky kit --><script src="https://cdnjs.cloudflare.com/ajax/libs/sticky-kit/1.1.3/sticky-kit.min.js" integrity="sha256-c4Rlo1ZozqTPE2RLuvbusY3+SU1pQaJC0TjuhygMipw=" crossorigin="anonymous"></script><!-- pkgdown --><link href="pkgdown.css" rel="stylesheet">
<script src="pkgdown.js"></script><meta property="og:title" content="Multivariate Regression">
<meta property="og:description" content="Implements high-dimensional multivariate regression by stacking (Rauschenberger et al. 2019).">
<meta property="og:description" content="Implements high-dimensional multivariate regression by stacked generalisation (Wolpert 1992 &lt;doi:10.1016/S0893-6080(05)80023-1&gt;). For positively correlated outcomes, a single multivariate regression is typically more predictive than multiple univariate regressions. Includes functions for model fitting, extracting coefficients, outcome prediction, and performance measurement.">
<meta name="twitter:card" content="summary">
<!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
<script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script>
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<div id="scope" class="section level2">
<h2 class="hasAnchor">
<a href="#scope" class="anchor"></a>Scope</h2>
<p>Stacked Elastic Net Regression (extending <a href="https://CRAN.R-project.org/package=glmnet">glmnet</a>).</p>
<p>Multivariate Elastic Net Regression (extending <a href="https://CRAN.R-project.org/package=glmnet">glmnet</a>).</p>
</div>
<div id="installation" class="section level2">
<h2 class="hasAnchor">
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