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

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