Armin Rauschenberger · Armin Rauschenberger · 3841a5fa · bb732a9c · 3841a5fa · 3841a5fa
20 changed files
--- a/.Rbuildignore
+++ b/.Rbuildignore
@@ -5,4 +5,3 @@
 ^cran-comments\.md$
 ^appveyor\.yml$
 ^\.Rhistory$
-^CRAN-RELEASE$
--- a/CRAN-RELEASE
+++ b/CRAN-RELEASE
-This package was submitted to CRAN on 2020-06-08.
-Once it is accepted, delete this file and tag the release (commit 79c29efcbc).
--- a/DESCRIPTION
+++ b/DESCRIPTION
 Package: starnet
-Version: 0.0.2
+Version: 0.0.3
 Title: Stacked Elastic Net
 Description: Implements stacked elastic net regression (Rauschenberger 2020, <doi:10.1093/bioinformatics/btaa535>). The elastic net generalises ridge and lasso regularisation (Zou 2005, <doi:10.1111/j.1467-9868.2005.00503.x>). Instead of fixing or tuning the mixing parameter alpha, we combine multiple alpha by stacked generalisation (Wolpert 1992 <doi:10.1016/S0893-6080(05)80023-1>).
 Depends: R (>= 3.0.0)

--- a/R/functions.R
+++ b/R/functions.R
@@ -84,14 +84,14 @@
 #' 
 #' @examples
 #' set.seed(1)
-#' n <- 40; p <- 50
+#' n <- 50; p <- 100
 #' y <- rnorm(n=n)
 #' X <- matrix(rnorm(n*p),nrow=n,ncol=p)
 #' object <- starnet(y=y,X=X,family="gaussian")
 #' 
 starnet <- function(y,X,family="gaussian",nalpha=21,alpha=NULL,nfolds=10,foldid=NULL,type.measure="deviance",alpha.meta=1,penalty.factor=NULL,intercept=NULL,upper.limit=NULL,unit.sum=NULL,...){
-  if(is.na(alpha.meta) & (!"CVXR" %in% .packages(all.available=TRUE))){
+  if(is.na(alpha.meta) && (!"CVXR" %in% .packages(all.available=TRUE))){
    stop("Install CVXR from CRAN for alpha.meta=NA.",call.=FALSE)
  }
@@ -317,7 +317,7 @@ starnet <- function(y,X,family="gaussian",nalpha=21,alpha=NULL,nfolds=10,foldid=
 #' 
 #' @examples
 #' set.seed(1)
-#' n <- 40; p <- 50
+#' n <- 50; p <- 100
 #' y <- rnorm(n=n)
 #' X <- matrix(rnorm(n*p),nrow=n,ncol=p)
 #' object <- starnet(y=y,X=X)
@@ -385,7 +385,7 @@ predict.starnet <- function(object,newx,type="response",nzero=NULL,...){
 #' 
 #' @examples
 #' set.seed(1)
-#' n <- 40; p <- 50
+#' n <- 50; p <- 100
 #' y <- rnorm(n=n)
 #' X <- matrix(rnorm(n*p),nrow=n,ncol=p)
 #' object <- starnet(y=y,X=X)
@@ -447,7 +447,7 @@ coef.starnet <- function(object,nzero=NULL,...){
 #' 
 #' @examples
 #' set.seed(1)
-#' n <- 40; p <- 50
+#' n <- 50; p <- 100
 #' y <- rnorm(n=n)
 #' X <- matrix(rnorm(n*p),nrow=n,ncol=p)
 #' object <- starnet(y=y,X=X)
@@ -481,7 +481,7 @@ weights.starnet <- function(object,...){
 #' 
 #' @examples
 #' set.seed(1)
-#' n <- 40; p <- 50
+#' n <- 50; p <- 100
 #' y <- rnorm(n=n)
 #' X <- matrix(rnorm(n*p),nrow=n,ncol=p)
 #' object <- starnet(y=y,X=X)

--- a/cran-comments.md
+++ b/cran-comments.md
 Reason for resubmission: error on r-patched-solaris-x86.
\ No newline at end of file
+(I actually think there is an issue with the R package glmnet.)
\ No newline at end of file
--- a/docs/articles/article.html
+++ b/docs/articles/article.html
@@ -89,7 +89,6 @@
-<p>The <code>starnet</code> manuscript is in preparation. Click <a href="https://CRAN.R-project.org/package=starnet">here</a> for the R package.</p>
 <p>Click <a href="https://academic.oup.com/bioinformatics/advance-article-pdf/doi/10.1093/bioinformatics/btaa535/33263777/btaa535.pdf">here</a> to download article.</p>
 <div>
 <object data="https://academic.oup.com/bioinformatics/advance-article-pdf/doi/10.1093/bioinformatics/btaa535/33263777/btaa535.pdf" type="application/pdf" width="100%" height="500px">

--- a/docs/articles/script.html
+++ b/docs/articles/script.html
@@ -82,7 +82,7 @@
      <h1 data-toc-skip>Stacked Elastic Net</h1>
                        <h4 class="author">Armin Rauschenberger</h4>
-            <h4 class="date">08 June 2020</h4>
+            <h4 class="date">10 June 2020</h4>
      <small class="dont-index">Source: <a href="https://github.com/rauschenberger/starnet/blob/master/vignettes/script.Rmd"><code>vignettes/script.Rmd</code></a></small>
      <div class="hidden name"><code>script.Rmd</code></div>

--- a/docs/pkgdown.yml
+++ b/docs/pkgdown.yml
@@ -5,5 +5,5 @@ articles:
  article: article.html
  script: script.html
  starnet: starnet.html
-last_built: 2020-06-08T06:25Z
+last_built: 2020-06-10T10:11Z
--- a/docs/reference/coef.starnet.html
+++ b/docs/reference/coef.starnet.html
@@ -160,7 +160,7 @@ respectively.</p>
    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
    <pre class="examples"><div class='input'><span class='fu'><a href='https://rdrr.io/r/base/Random.html'>set.seed</a></span>(<span class='fl'>1</span>)
-<span class='no'>n</span> <span class='kw'>&lt;-</span> <span class='fl'>40</span>; <span class='no'>p</span> <span class='kw'>&lt;-</span> <span class='fl'>50</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'>y</span> <span class='kw'>&lt;-</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='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'>object</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='starnet.html'>starnet</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>)

--- a/docs/reference/predict.starnet.html
+++ b/docs/reference/predict.starnet.html
@@ -173,7 +173,7 @@ and <code>none</code> (intercept-only model).</p>
    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
    <pre class="examples"><div class='input'><span class='fu'><a href='https://rdrr.io/r/base/Random.html'>set.seed</a></span>(<span class='fl'>1</span>)
-<span class='no'>n</span> <span class='kw'>&lt;-</span> <span class='fl'>40</span>; <span class='no'>p</span> <span class='kw'>&lt;-</span> <span class='fl'>50</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'>y</span> <span class='kw'>&lt;-</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='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'>object</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='starnet.html'>starnet</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>)

--- a/docs/reference/print.starnet.html
+++ b/docs/reference/print.starnet.html
@@ -151,7 +151,7 @@
    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
    <pre class="examples"><div class='input'><span class='fu'><a href='https://rdrr.io/r/base/Random.html'>set.seed</a></span>(<span class='fl'>1</span>)
-<span class='no'>n</span> <span class='kw'>&lt;-</span> <span class='fl'>40</span>; <span class='no'>p</span> <span class='kw'>&lt;-</span> <span class='fl'>50</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'>y</span> <span class='kw'>&lt;-</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='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'>object</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='starnet.html'>starnet</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>)

--- a/docs/reference/starnet-package-1.png
+++ b/docs/reference/starnet-package-1.png
--- a/docs/reference/starnet.html
+++ b/docs/reference/starnet.html
@@ -241,7 +241,7 @@ doi: <a href='https://doi.org/10.1093/bioinformatics/btaa535'>10.1093/bioinforma
    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
    <pre class="examples"><div class='input'><span class='fu'><a href='https://rdrr.io/r/base/Random.html'>set.seed</a></span>(<span class='fl'>1</span>)
-<span class='no'>n</span> <span class='kw'>&lt;-</span> <span class='fl'>40</span>; <span class='no'>p</span> <span class='kw'>&lt;-</span> <span class='fl'>50</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'>y</span> <span class='kw'>&lt;-</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='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'>object</span> <span class='kw'>&lt;-</span> <span class='fu'>starnet</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='st'>"gaussian"</span>)</div></pre>

--- a/docs/reference/weights.starnet.html
+++ b/docs/reference/weights.starnet.html
@@ -153,18 +153,18 @@ i.e. the weights for the base learners.</p>
    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
    <pre class="examples"><div class='input'><span class='fu'><a href='https://rdrr.io/r/base/Random.html'>set.seed</a></span>(<span class='fl'>1</span>)
-<span class='no'>n</span> <span class='kw'>&lt;-</span> <span class='fl'>40</span>; <span class='no'>p</span> <span class='kw'>&lt;-</span> <span class='fl'>50</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'>y</span> <span class='kw'>&lt;-</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='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'>object</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='starnet.html'>starnet</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; (Intercept)          V1          V2          V3          V4          V5 
-#&gt;  0.06032819  0.00000000  0.23525906  0.15396683  0.00000000  0.00000000 
+#&gt;   0.1004483   0.0000000   0.0000000   0.0000000   0.0000000   0.0000000 
 #&gt;          V6          V7          V8          V9         V10         V11 
-#&gt;  0.00000000  0.00000000  0.00000000  0.00000000  0.00000000  0.00000000 
+#&gt;   0.0000000   0.0000000   0.0000000   0.0000000   0.0000000   0.0000000 
 #&gt;         V12         V13         V14         V15         V16         V17 
-#&gt;  0.00000000  0.00000000  0.00000000  0.00000000  0.00000000  0.00000000 
+#&gt;   0.0000000   0.0000000   0.0000000   0.0000000   0.0000000   0.0000000 
 #&gt;         V18         V19         V20         V21 
-#&gt;  0.00000000  0.00000000  0.00000000  0.00000000 </div><div class='input'>
+#&gt;   0.0000000   0.0000000   0.0000000   0.0000000 </div><div class='input'>
 </div></pre>
  </div>
  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">

--- a/man/coef.starnet.Rd
+++ b/man/coef.starnet.Rd
@@ -25,7 +25,7 @@ Extracts pooled coefficients.
 }
 \examples{
 set.seed(1)
-n <- 40; p <- 50
+n <- 50; p <- 100
 y <- rnorm(n=n)
 X <- matrix(rnorm(n*p),nrow=n,ncol=p)
 object <- starnet(y=y,X=X)

--- a/man/predict.starnet.Rd
+++ b/man/predict.starnet.Rd
@@ -35,7 +35,7 @@ Predicts outcome from features with stacked model.
 }
 \examples{
 set.seed(1)
-n <- 40; p <- 50
+n <- 50; p <- 100
 y <- rnorm(n=n)
 X <- matrix(rnorm(n*p),nrow=n,ncol=p)
 object <- starnet(y=y,X=X)

--- a/man/print.starnet.Rd
+++ b/man/print.starnet.Rd
@@ -19,7 +19,7 @@ Prints object of class \link[starnet]{starnet}.
 }
 \examples{
 set.seed(1)
-n <- 40; p <- 50
+n <- 50; p <- 100
 y <- rnorm(n=n)
 X <- matrix(rnorm(n*p),nrow=n,ncol=p)
 object <- starnet(y=y,X=X)

--- a/man/starnet.Rd
+++ b/man/starnet.Rd
@@ -82,7 +82,7 @@ argument \code{nzero} in functions
 }
 \examples{
 set.seed(1)
-n <- 40; p <- 50
+n <- 50; p <- 100
 y <- rnorm(n=n)
 X <- matrix(rnorm(n*p),nrow=n,ncol=p)
 object <- starnet(y=y,X=X,family="gaussian")

--- a/man/weights.starnet.Rd
+++ b/man/weights.starnet.Rd
@@ -20,7 +20,7 @@ i.e. the weights for the base learners.
 }
 \examples{
 set.seed(1)
-n <- 40; p <- 50
+n <- 50; p <- 100
 y <- rnorm(n=n)
 X <- matrix(rnorm(n*p),nrow=n,ncol=p)
 object <- starnet(y=y,X=X)

--- a/tests/testthat/test.R
+++ b/tests/testthat/test.R
 for(family in c("gaussian","binomial","poisson")){
-  n <- 30; p <- 50
+  n <- 50; p <- 100 # was 30 and 50
  if(family=="cox"){
    list <- list()
    list$y <- survival::Surv(time=abs(rnorm(n)),