Commit 15aecf6a authored by Armin Rauschenberger's avatar Armin Rauschenberger

vignette

parent b9c0eead
This package was submitted to CRAN on 2020-10-21.
Once it is accepted, delete this file and tag the release (commit 8eb7bf5).
......@@ -89,15 +89,12 @@
#' n <- 50; p <- 100; q <- 3
#' X <- matrix(rnorm(n*p),nrow=n,ncol=p)
#' Y <- replicate(n=q,expr=rnorm(n=n,mean=rowSums(X[,1:5])))
#' object <- joinet(Y=Y,X=X)
#' }}
#'
#' object <- joinet(Y=Y,X=X)}}
#' \dontrun{
#' n <- 50; p <- 100; q <- 3
#' X <- matrix(rnorm(n*p),nrow=n,ncol=p)
#' Y <- replicate(n=q,expr=rnorm(n=n,mean=rowSums(X[,1:5])))
#' object <- joinet(Y=Y,X=X)
#' }
#' object <- joinet(Y=Y,X=X)}
#'
#' \dontrun{
#' browseVignettes("joinet") # further examples}
......@@ -284,14 +281,21 @@ joinet <- function(Y,X,family="gaussian",nfolds=10,foldid=NULL,type.measure="dev
#' with \eqn{n} rows (samples) and \eqn{q} columns (variables).
#'
#' @examples
#' \dontshow{
#' if(!grepl('SunOS',Sys.info()['sysname'])){
#' n <- 50; p <- 100; q <- 3
#' X <- matrix(rnorm(n*p),nrow=n,ncol=p)
#' Y <- replicate(n=q,expr=rnorm(n=n,mean=rowSums(X[,1:5])))
#' Y[,1] <- 1*(Y[,1]>median(Y[,1]))
#' object <- joinet(Y=Y,X=X,family=c("binomial","gaussian","gaussian"))
#' predict(object,newx=X)
#' }
#' predict(object,newx=X)}}
#' \dontrun{
#' n <- 50; p <- 100; q <- 3
#' X <- matrix(rnorm(n*p),nrow=n,ncol=p)
#' Y <- replicate(n=q,expr=rnorm(n=n,mean=rowSums(X[,1:5])))
#' Y[,1] <- 1*(Y[,1]>median(Y[,1]))
#' object <- joinet(Y=Y,X=X,family=c("binomial","gaussian","gaussian"))
#' predict(object,newx=X)}
#'
predict.joinet <- function(object,newx,type="response",...){
if(length(list(...))!=0){warning("Ignoring argument.",call.=FALSE)}
......@@ -357,13 +361,19 @@ predict.joinet <- function(object,newx,type="response",...){
#' in a matrix with \eqn{p} rows (inputs) and \eqn{q} columns.
#'
#' @examples
#' \dontshow{
#' if(!grepl('SunOS',Sys.info()['sysname'])){
#' n <- 50; p <- 100; q <- 3
#' X <- matrix(rnorm(n*p),nrow=n,ncol=p)
#' Y <- replicate(n=q,expr=rnorm(n=n,mean=rowSums(X[,1:5])))
#' object <- joinet(Y=Y,X=X)
#' coef <- coef(object)
#' }
#' coef <- coef(object)}}
#' \dontrun{
#' n <- 50; p <- 100; q <- 3
#' X <- matrix(rnorm(n*p),nrow=n,ncol=p)
#' Y <- replicate(n=q,expr=rnorm(n=n,mean=rowSums(X[,1:5])))
#' object <- joinet(Y=Y,X=X)
#' coef <- coef(object)}
#'
coef.joinet <- function(object,...){
if(length(list(...))!=0){warning("Ignoring argument.",call.=FALSE)}
......@@ -426,13 +436,19 @@ coef.joinet <- function(object,...){
#' in the row on the outcomes in the column.
#'
#' @examples
#' \dontshow{
#' if(!grepl('SunOS',Sys.info()['sysname'])){
#' n <- 50; p <- 100; q <- 3
#' X <- matrix(rnorm(n*p),nrow=n,ncol=p)
#' Y <- replicate(n=q,expr=rnorm(n=n,mean=rowSums(X[,1:5])))
#' object <- joinet(Y=Y,X=X)
#' weights(object)
#' }
#' weights(object)}}
#' \dontrun{
#' n <- 50; p <- 100; q <- 3
#' X <- matrix(rnorm(n*p),nrow=n,ncol=p)
#' Y <- replicate(n=q,expr=rnorm(n=n,mean=rowSums(X[,1:5])))
#' object <- joinet(Y=Y,X=X)
#' weights(object)}
#'
weights.joinet <- function(object,...){
if(length(list(...))!=0){warning("Ignoring argument.",call.=FALSE)}
......@@ -505,12 +521,17 @@ print.joinet <- function(x,...){
#' and the intercept-only models (\code{none}).
#'
#' @examples
#' \dontshow{
#' if(!grepl('SunOS',Sys.info()['sysname'])){
#' n <- 50; p <- 100; q <- 3
#' X <- matrix(rnorm(n*p),nrow=n,ncol=p)
#' Y <- replicate(n=q,expr=rnorm(n=n,mean=rowSums(X[,1:5])))
#' cv.joinet(Y=Y,X=X)
#' }
#' cv.joinet(Y=Y,X=X)}}
#' \dontrun{
#' n <- 50; p <- 100; q <- 3
#' X <- matrix(rnorm(n*p),nrow=n,ncol=p)
#' Y <- replicate(n=q,expr=rnorm(n=n,mean=rowSums(X[,1:5])))
#' cv.joinet(Y=Y,X=X)}
#'
#' \dontrun{
#' # correlated features
......
......@@ -4,5 +4,5 @@ pkgdown_sha: ~
articles:
article: article.html
joinet: joinet.html
last_built: 2020-11-03T08:27Z
last_built: 2020-11-03T08:45Z
......@@ -155,13 +155,19 @@ and the slot <code>beta</code> contains the slopes
in a matrix with \(p\) rows (inputs) and \(q\) columns.</p>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><div class='input'><span class='kw'>if</span>(!<span class='fu'><a href='https://rdrr.io/r/base/grep.html'>grepl</a></span>(<span class='st'>'SunOS'</span>,<span class='fu'><a href='https://rdrr.io/r/base/Sys.info.html'>Sys.info</a></span>()[<span class='st'>'sysname'</span>])){
<pre class="examples"><div class='input'><span class='co'># \dontshow{</span>
<span class='kw'>if</span>(!<span class='fu'><a href='https://rdrr.io/r/base/grep.html'>grepl</a></span>(<span class='st'>'SunOS'</span>,<span class='fu'><a href='https://rdrr.io/r/base/Sys.info.html'>Sys.info</a></span>()[<span class='st'>'sysname'</span>])){
<span class='no'>n</span> <span class='kw'>&lt;-</span> <span class='fl'>50</span>; <span class='no'>p</span> <span class='kw'>&lt;-</span> <span class='fl'>100</span>; <span class='no'>q</span> <span class='kw'>&lt;-</span> <span class='fl'>3</span>
<span class='no'>X</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/matrix.html'>matrix</a></span>(<span class='fu'><a href='https://rdrr.io/r/stats/Normal.html'>rnorm</a></span>(<span class='no'>n</span>*<span class='no'>p</span>),<span class='kw'>nrow</span><span class='kw'>=</span><span class='no'>n</span>,<span class='kw'>ncol</span><span class='kw'>=</span><span class='no'>p</span>)
<span class='no'>Y</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/lapply.html'>replicate</a></span>(<span class='kw'>n</span><span class='kw'>=</span><span class='no'>q</span>,<span class='kw'>expr</span><span class='kw'>=</span><span class='fu'><a href='https://rdrr.io/r/stats/Normal.html'>rnorm</a></span>(<span class='kw'>n</span><span class='kw'>=</span><span class='no'>n</span>,<span class='kw'>mean</span><span class='kw'>=</span><span class='fu'><a href='https://rdrr.io/r/base/colSums.html'>rowSums</a></span>(<span class='no'>X</span>[,<span class='fl'>1</span>:<span class='fl'>5</span>])))
<span class='no'>object</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='joinet.html'>joinet</a></span>(<span class='kw'>Y</span><span class='kw'>=</span><span class='no'>Y</span>,<span class='kw'>X</span><span class='kw'>=</span><span class='no'>X</span>)
<span class='no'>coef</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/stats/coef.html'>coef</a></span>(<span class='no'>object</span>)
}</div></pre>
<span class='no'>coef</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/stats/coef.html'>coef</a></span>(<span class='no'>object</span>)}<span class='co'># }</span>
<span class='kw'>if</span> (<span class='fl'>FALSE</span>) {
<span class='no'>n</span> <span class='kw'>&lt;-</span> <span class='fl'>50</span>; <span class='no'>p</span> <span class='kw'>&lt;-</span> <span class='fl'>100</span>; <span class='no'>q</span> <span class='kw'>&lt;-</span> <span class='fl'>3</span>
<span class='no'>X</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/matrix.html'>matrix</a></span>(<span class='fu'><a href='https://rdrr.io/r/stats/Normal.html'>rnorm</a></span>(<span class='no'>n</span>*<span class='no'>p</span>),<span class='kw'>nrow</span><span class='kw'>=</span><span class='no'>n</span>,<span class='kw'>ncol</span><span class='kw'>=</span><span class='no'>p</span>)
<span class='no'>Y</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/lapply.html'>replicate</a></span>(<span class='kw'>n</span><span class='kw'>=</span><span class='no'>q</span>,<span class='kw'>expr</span><span class='kw'>=</span><span class='fu'><a href='https://rdrr.io/r/stats/Normal.html'>rnorm</a></span>(<span class='kw'>n</span><span class='kw'>=</span><span class='no'>n</span>,<span class='kw'>mean</span><span class='kw'>=</span><span class='fu'><a href='https://rdrr.io/r/base/colSums.html'>rowSums</a></span>(<span class='no'>X</span>[,<span class='fl'>1</span>:<span class='fl'>5</span>])))
<span class='no'>object</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='joinet.html'>joinet</a></span>(<span class='kw'>Y</span><span class='kw'>=</span><span class='no'>Y</span>,<span class='kw'>X</span><span class='kw'>=</span><span class='no'>X</span>)
<span class='no'>coef</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/stats/coef.html'>coef</a></span>(<span class='no'>object</span>)}</div></pre>
</div>
<div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
<nav id="toc" data-toggle="toc" class="sticky-top">
......
......@@ -159,14 +159,14 @@ The slots <code>base</code> and <code>meta</code> each contain a matrix
with \(n\) rows (samples) and \(q\) columns (variables).</p>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><div class='input'><span class='kw'>if</span>(!<span class='fu'><a href='https://rdrr.io/r/base/grep.html'>grepl</a></span>(<span class='st'>'SunOS'</span>,<span class='fu'><a href='https://rdrr.io/r/base/Sys.info.html'>Sys.info</a></span>()[<span class='st'>'sysname'</span>])){
<pre class="examples"><div class='input'><span class='co'># \dontshow{</span>
<span class='kw'>if</span>(!<span class='fu'><a href='https://rdrr.io/r/base/grep.html'>grepl</a></span>(<span class='st'>'SunOS'</span>,<span class='fu'><a href='https://rdrr.io/r/base/Sys.info.html'>Sys.info</a></span>()[<span class='st'>'sysname'</span>])){
<span class='no'>n</span> <span class='kw'>&lt;-</span> <span class='fl'>50</span>; <span class='no'>p</span> <span class='kw'>&lt;-</span> <span class='fl'>100</span>; <span class='no'>q</span> <span class='kw'>&lt;-</span> <span class='fl'>3</span>
<span class='no'>X</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/matrix.html'>matrix</a></span>(<span class='fu'><a href='https://rdrr.io/r/stats/Normal.html'>rnorm</a></span>(<span class='no'>n</span>*<span class='no'>p</span>),<span class='kw'>nrow</span><span class='kw'>=</span><span class='no'>n</span>,<span class='kw'>ncol</span><span class='kw'>=</span><span class='no'>p</span>)
<span class='no'>Y</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/lapply.html'>replicate</a></span>(<span class='kw'>n</span><span class='kw'>=</span><span class='no'>q</span>,<span class='kw'>expr</span><span class='kw'>=</span><span class='fu'><a href='https://rdrr.io/r/stats/Normal.html'>rnorm</a></span>(<span class='kw'>n</span><span class='kw'>=</span><span class='no'>n</span>,<span class='kw'>mean</span><span class='kw'>=</span><span class='fu'><a href='https://rdrr.io/r/base/colSums.html'>rowSums</a></span>(<span class='no'>X</span>[,<span class='fl'>1</span>:<span class='fl'>5</span>])))
<span class='no'>Y</span>[,<span class='fl'>1</span>] <span class='kw'>&lt;-</span> <span class='fl'>1</span>*(<span class='no'>Y</span>[,<span class='fl'>1</span>]<span class='kw'>&gt;</span><span class='fu'><a href='https://rdrr.io/r/stats/median.html'>median</a></span>(<span class='no'>Y</span>[,<span class='fl'>1</span>]))
<span class='no'>object</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='joinet.html'>joinet</a></span>(<span class='kw'>Y</span><span class='kw'>=</span><span class='no'>Y</span>,<span class='kw'>X</span><span class='kw'>=</span><span class='no'>X</span>,<span class='kw'>family</span><span class='kw'>=</span><span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"binomial"</span>,<span class='st'>"gaussian"</span>,<span class='st'>"gaussian"</span>))
<span class='fu'><a href='https://rdrr.io/r/stats/predict.html'>predict</a></span>(<span class='no'>object</span>,<span class='kw'>newx</span><span class='kw'>=</span><span class='no'>X</span>)
}</div><div class='output co'>#&gt; $base
<span class='fu'><a href='https://rdrr.io/r/stats/predict.html'>predict</a></span>(<span class='no'>object</span>,<span class='kw'>newx</span><span class='kw'>=</span><span class='no'>X</span>)}<span class='co'># }</span></div><div class='output co'>#&gt; $base
#&gt; [,1] [,2] [,3]
#&gt; [1,] 0.41837245 -1.928585385 -2.49734037
#&gt; [2,] 0.73430703 -1.232615541 -1.92258279
......@@ -271,8 +271,13 @@ with \(n\) rows (samples) and \(q\) columns (variables).</p>
#&gt; [48,] 0.07567690 -3.2214496 -3.11672913
#&gt; [49,] 0.58299820 -0.1185430 -0.03693255
#&gt; [50,] 0.42367190 -0.9519434 -1.64962005
#&gt; </div><div class='input'>
</div></pre>
#&gt; </div><div class='input'><span class='kw'>if</span> (<span class='fl'>FALSE</span>) {
<span class='no'>n</span> <span class='kw'>&lt;-</span> <span class='fl'>50</span>; <span class='no'>p</span> <span class='kw'>&lt;-</span> <span class='fl'>100</span>; <span class='no'>q</span> <span class='kw'>&lt;-</span> <span class='fl'>3</span>
<span class='no'>X</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/matrix.html'>matrix</a></span>(<span class='fu'><a href='https://rdrr.io/r/stats/Normal.html'>rnorm</a></span>(<span class='no'>n</span>*<span class='no'>p</span>),<span class='kw'>nrow</span><span class='kw'>=</span><span class='no'>n</span>,<span class='kw'>ncol</span><span class='kw'>=</span><span class='no'>p</span>)
<span class='no'>Y</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/lapply.html'>replicate</a></span>(<span class='kw'>n</span><span class='kw'>=</span><span class='no'>q</span>,<span class='kw'>expr</span><span class='kw'>=</span><span class='fu'><a href='https://rdrr.io/r/stats/Normal.html'>rnorm</a></span>(<span class='kw'>n</span><span class='kw'>=</span><span class='no'>n</span>,<span class='kw'>mean</span><span class='kw'>=</span><span class='fu'><a href='https://rdrr.io/r/base/colSums.html'>rowSums</a></span>(<span class='no'>X</span>[,<span class='fl'>1</span>:<span class='fl'>5</span>])))
<span class='no'>Y</span>[,<span class='fl'>1</span>] <span class='kw'>&lt;-</span> <span class='fl'>1</span>*(<span class='no'>Y</span>[,<span class='fl'>1</span>]<span class='kw'>&gt;</span><span class='fu'><a href='https://rdrr.io/r/stats/median.html'>median</a></span>(<span class='no'>Y</span>[,<span class='fl'>1</span>]))
<span class='no'>object</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='joinet.html'>joinet</a></span>(<span class='kw'>Y</span><span class='kw'>=</span><span class='no'>Y</span>,<span class='kw'>X</span><span class='kw'>=</span><span class='no'>X</span>,<span class='kw'>family</span><span class='kw'>=</span><span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"binomial"</span>,<span class='st'>"gaussian"</span>,<span class='st'>"gaussian"</span>))
<span class='fu'><a href='https://rdrr.io/r/stats/predict.html'>predict</a></span>(<span class='no'>object</span>,<span class='kw'>newx</span><span class='kw'>=</span><span class='no'>X</span>)}</div></pre>
</div>
<div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
<nav id="toc" data-toggle="toc" class="sticky-top">
......
......@@ -154,18 +154,22 @@ which are the effects of the outcomes
in the row on the outcomes in the column.</p>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><div class='input'><span class='kw'>if</span>(!<span class='fu'><a href='https://rdrr.io/r/base/grep.html'>grepl</a></span>(<span class='st'>'SunOS'</span>,<span class='fu'><a href='https://rdrr.io/r/base/Sys.info.html'>Sys.info</a></span>()[<span class='st'>'sysname'</span>])){
<pre class="examples"><div class='input'><span class='co'># \dontshow{</span>
<span class='kw'>if</span>(!<span class='fu'><a href='https://rdrr.io/r/base/grep.html'>grepl</a></span>(<span class='st'>'SunOS'</span>,<span class='fu'><a href='https://rdrr.io/r/base/Sys.info.html'>Sys.info</a></span>()[<span class='st'>'sysname'</span>])){
<span class='no'>n</span> <span class='kw'>&lt;-</span> <span class='fl'>50</span>; <span class='no'>p</span> <span class='kw'>&lt;-</span> <span class='fl'>100</span>; <span class='no'>q</span> <span class='kw'>&lt;-</span> <span class='fl'>3</span>
<span class='no'>X</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/matrix.html'>matrix</a></span>(<span class='fu'><a href='https://rdrr.io/r/stats/Normal.html'>rnorm</a></span>(<span class='no'>n</span>*<span class='no'>p</span>),<span class='kw'>nrow</span><span class='kw'>=</span><span class='no'>n</span>,<span class='kw'>ncol</span><span class='kw'>=</span><span class='no'>p</span>)
<span class='no'>Y</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/lapply.html'>replicate</a></span>(<span class='kw'>n</span><span class='kw'>=</span><span class='no'>q</span>,<span class='kw'>expr</span><span class='kw'>=</span><span class='fu'><a href='https://rdrr.io/r/stats/Normal.html'>rnorm</a></span>(<span class='kw'>n</span><span class='kw'>=</span><span class='no'>n</span>,<span class='kw'>mean</span><span class='kw'>=</span><span class='fu'><a href='https://rdrr.io/r/base/colSums.html'>rowSums</a></span>(<span class='no'>X</span>[,<span class='fl'>1</span>:<span class='fl'>5</span>])))
<span class='no'>object</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='joinet.html'>joinet</a></span>(<span class='kw'>Y</span><span class='kw'>=</span><span class='no'>Y</span>,<span class='kw'>X</span><span class='kw'>=</span><span class='no'>X</span>)
<span class='fu'><a href='https://rdrr.io/r/stats/weights.html'>weights</a></span>(<span class='no'>object</span>)
}</div><div class='output co'>#&gt; y1 y2 y3
<span class='fu'><a href='https://rdrr.io/r/stats/weights.html'>weights</a></span>(<span class='no'>object</span>)}<span class='co'># }</span></div><div class='output co'>#&gt; y1 y2 y3
#&gt; (Intercept) -0.04720442 -0.15165929 0.26901703
#&gt; V1 0.00000000 0.01158793 0.65726908
#&gt; V2 0.55230103 0.71134918 0.45932382
#&gt; V3 0.60228936 0.49505561 0.01764908</div><div class='input'>
</div></pre>
#&gt; V3 0.60228936 0.49505561 0.01764908</div><div class='input'><span class='kw'>if</span> (<span class='fl'>FALSE</span>) {
<span class='no'>n</span> <span class='kw'>&lt;-</span> <span class='fl'>50</span>; <span class='no'>p</span> <span class='kw'>&lt;-</span> <span class='fl'>100</span>; <span class='no'>q</span> <span class='kw'>&lt;-</span> <span class='fl'>3</span>
<span class='no'>X</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/matrix.html'>matrix</a></span>(<span class='fu'><a href='https://rdrr.io/r/stats/Normal.html'>rnorm</a></span>(<span class='no'>n</span>*<span class='no'>p</span>),<span class='kw'>nrow</span><span class='kw'>=</span><span class='no'>n</span>,<span class='kw'>ncol</span><span class='kw'>=</span><span class='no'>p</span>)
<span class='no'>Y</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/lapply.html'>replicate</a></span>(<span class='kw'>n</span><span class='kw'>=</span><span class='no'>q</span>,<span class='kw'>expr</span><span class='kw'>=</span><span class='fu'><a href='https://rdrr.io/r/stats/Normal.html'>rnorm</a></span>(<span class='kw'>n</span><span class='kw'>=</span><span class='no'>n</span>,<span class='kw'>mean</span><span class='kw'>=</span><span class='fu'><a href='https://rdrr.io/r/base/colSums.html'>rowSums</a></span>(<span class='no'>X</span>[,<span class='fl'>1</span>:<span class='fl'>5</span>])))
<span class='no'>object</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='joinet.html'>joinet</a></span>(<span class='kw'>Y</span><span class='kw'>=</span><span class='no'>Y</span>,<span class='kw'>X</span><span class='kw'>=</span><span class='no'>X</span>)
<span class='fu'><a href='https://rdrr.io/r/stats/weights.html'>weights</a></span>(<span class='no'>object</span>)}</div></pre>
</div>
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......
......@@ -24,12 +24,18 @@ Extracts pooled coefficients.
the coefficients from the base learners.)
}
\examples{
\dontshow{
if(!grepl('SunOS',Sys.info()['sysname'])){
n <- 50; p <- 100; q <- 3
X <- matrix(rnorm(n*p),nrow=n,ncol=p)
Y <- replicate(n=q,expr=rnorm(n=n,mean=rowSums(X[,1:5])))
object <- joinet(Y=Y,X=X)
coef <- coef(object)
}
coef <- coef(object)}}
\dontrun{
n <- 50; p <- 100; q <- 3
X <- matrix(rnorm(n*p),nrow=n,ncol=p)
Y <- replicate(n=q,expr=rnorm(n=n,mean=rowSums(X[,1:5])))
object <- joinet(Y=Y,X=X)
coef <- coef(object)}
}
......@@ -87,12 +87,17 @@ and the intercept-only models (\code{none}).
Compares univariate and multivariate regression.
}
\examples{
\dontshow{
if(!grepl('SunOS',Sys.info()['sysname'])){
n <- 50; p <- 100; q <- 3
X <- matrix(rnorm(n*p),nrow=n,ncol=p)
Y <- replicate(n=q,expr=rnorm(n=n,mean=rowSums(X[,1:5])))
cv.joinet(Y=Y,X=X)
}
cv.joinet(Y=Y,X=X)}}
\dontrun{
n <- 50; p <- 100; q <- 3
X <- matrix(rnorm(n*p),nrow=n,ncol=p)
Y <- replicate(n=q,expr=rnorm(n=n,mean=rowSums(X[,1:5])))
cv.joinet(Y=Y,X=X)}
\dontrun{
# correlated features
......
......@@ -78,15 +78,12 @@ if(!grepl('SunOS',Sys.info()['sysname'])){
n <- 50; p <- 100; q <- 3
X <- matrix(rnorm(n*p),nrow=n,ncol=p)
Y <- replicate(n=q,expr=rnorm(n=n,mean=rowSums(X[,1:5])))
object <- joinet(Y=Y,X=X)
}}
object <- joinet(Y=Y,X=X)}}
\dontrun{
n <- 50; p <- 100; q <- 3
X <- matrix(rnorm(n*p),nrow=n,ncol=p)
Y <- replicate(n=q,expr=rnorm(n=n,mean=rowSums(X[,1:5])))
object <- joinet(Y=Y,X=X)
}
object <- joinet(Y=Y,X=X)}
\dontrun{
browseVignettes("joinet") # further examples}
......
......@@ -26,13 +26,20 @@ with \eqn{n} rows (samples) and \eqn{q} columns (variables).
Predicts outcome from features with stacked model.
}
\examples{
\dontshow{
if(!grepl('SunOS',Sys.info()['sysname'])){
n <- 50; p <- 100; q <- 3
X <- matrix(rnorm(n*p),nrow=n,ncol=p)
Y <- replicate(n=q,expr=rnorm(n=n,mean=rowSums(X[,1:5])))
Y[,1] <- 1*(Y[,1]>median(Y[,1]))
object <- joinet(Y=Y,X=X,family=c("binomial","gaussian","gaussian"))
predict(object,newx=X)
}
predict(object,newx=X)}}
\dontrun{
n <- 50; p <- 100; q <- 3
X <- matrix(rnorm(n*p),nrow=n,ncol=p)
Y <- replicate(n=q,expr=rnorm(n=n,mean=rowSums(X[,1:5])))
Y[,1] <- 1*(Y[,1]>median(Y[,1]))
object <- joinet(Y=Y,X=X,family=c("binomial","gaussian","gaussian"))
predict(object,newx=X)}
}
......@@ -24,12 +24,18 @@ Extracts coefficients from the meta learner,
i.e. the weights for the base learners.
}
\examples{
\dontshow{
if(!grepl('SunOS',Sys.info()['sysname'])){
n <- 50; p <- 100; q <- 3
X <- matrix(rnorm(n*p),nrow=n,ncol=p)
Y <- replicate(n=q,expr=rnorm(n=n,mean=rowSums(X[,1:5])))
object <- joinet(Y=Y,X=X)
weights(object)
}
weights(object)}}
\dontrun{
n <- 50; p <- 100; q <- 3
X <- matrix(rnorm(n*p),nrow=n,ncol=p)
Y <- replicate(n=q,expr=rnorm(n=n,mean=rowSums(X[,1:5])))
object <- joinet(Y=Y,X=X)
weights(object)}
}
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