Commit 88a0538f authored by Armin Rauschenberger's avatar Armin Rauschenberger
Browse files

automation

parent 3c3ce35e
...@@ -10,6 +10,7 @@ Authors@R: person("Armin","Rauschenberger",email="a.rauschenberger@vumc.nl",role ...@@ -10,6 +10,7 @@ Authors@R: person("Armin","Rauschenberger",email="a.rauschenberger@vumc.nl",role
VignetteBuilder: knitr VignetteBuilder: knitr
License: GPL-3 License: GPL-3
LazyData: true LazyData: true
Language: en-GB
RoxygenNote: 6.1.1 RoxygenNote: 6.1.1
URL: https://github.com/rauschenberger/cornet URL: https://github.com/rauschenberger/cornet
BugReports: https://github.com/rauschenberger/cornet/issues BugReports: https://github.com/rauschenberger/cornet/issues
...@@ -15,7 +15,7 @@ ...@@ -15,7 +15,7 @@
#' vector of length \eqn{n} #' vector of length \eqn{n}
#' #'
#' @param cutoff #' @param cutoff
#' cutoff point for dichotomising outcome into classes\strong{:} #' cut-off point for dichotomising outcome into classes\strong{:}
#' \emph{meaningful} value between \code{min(y)} and \code{max(y)} #' \emph{meaningful} value between \code{min(y)} and \code{max(y)}
#' #'
#' @param X #' @param X
...@@ -575,7 +575,7 @@ predict.cornet <- function(object,newx,type="probability",...){ ...@@ -575,7 +575,7 @@ predict.cornet <- function(object,newx,type="probability",...){
#' Performance measurement by cross-validation #' Performance measurement by cross-validation
#' #'
#' @description #' @description
#' Compares models for a continuous response with a cutoff value. #' Compares models for a continuous response with a cut-off value.
#' #'
#' @details #' @details
#' Uses k-fold cross-validation, #' Uses k-fold cross-validation,
...@@ -647,7 +647,7 @@ predict.cornet <- function(object,newx,type="probability",...){ ...@@ -647,7 +647,7 @@ predict.cornet <- function(object,newx,type="probability",...){
#' Single-split test #' Single-split test
#' #'
#' @description #' @description
#' Compares models for a continuous response with a cutoff value. #' Compares models for a continuous response with a cut-off value.
#' #'
#' @details #' @details
#' Splits samples into 80% for training and 20% for testing, #' Splits samples into 80% for training and 20% for testing,
......
...@@ -141,7 +141,7 @@ vector of length \(n\)</p></td> ...@@ -141,7 +141,7 @@ vector of length \(n\)</p></td>
</tr> </tr>
<tr> <tr>
<th>cutoff</th> <th>cutoff</th>
<td><p>cutoff point for dichotomising outcome into classes<strong>:</strong> <td><p>cut-off point for dichotomising outcome into classes<strong>:</strong>
<em>meaningful</em> value between <code><a href='https://www.rdocumentation.org/packages/base/topics/Extremes'>min(y)</a></code> and <code><a href='https://www.rdocumentation.org/packages/base/topics/Extremes'>max(y)</a></code></p></td> <em>meaningful</em> value between <code><a href='https://www.rdocumentation.org/packages/base/topics/Extremes'>min(y)</a></code> and <code><a href='https://www.rdocumentation.org/packages/base/topics/Extremes'>max(y)</a></code></p></td>
</tr> </tr>
<tr> <tr>
......
...@@ -32,7 +32,7 @@ ...@@ -32,7 +32,7 @@
<meta property="og:title" content="Performance measurement by cross-validation — .compare" /> <meta property="og:title" content="Performance measurement by cross-validation — .compare" />
<meta property="og:description" content="Compares models for a continuous response with a cutoff value." /> <meta property="og:description" content="Compares models for a continuous response with a cut-off value." />
<meta name="twitter:card" content="summary" /> <meta name="twitter:card" content="summary" />
...@@ -121,7 +121,7 @@ ...@@ -121,7 +121,7 @@
<div class="ref-description"> <div class="ref-description">
<p>Compares models for a continuous response with a cutoff value.</p> <p>Compares models for a continuous response with a cut-off value.</p>
</div> </div>
...@@ -138,7 +138,7 @@ vector of length \(n\)</p></td> ...@@ -138,7 +138,7 @@ vector of length \(n\)</p></td>
</tr> </tr>
<tr> <tr>
<th>cutoff</th> <th>cutoff</th>
<td><p>cutoff point for dichotomising outcome into classes<strong>:</strong> <td><p>cut-off point for dichotomising outcome into classes<strong>:</strong>
<em>meaningful</em> value between <code><a href='https://www.rdocumentation.org/packages/base/topics/Extremes'>min(y)</a></code> and <code><a href='https://www.rdocumentation.org/packages/base/topics/Extremes'>max(y)</a></code></p></td> <em>meaningful</em> value between <code><a href='https://www.rdocumentation.org/packages/base/topics/Extremes'>min(y)</a></code> and <code><a href='https://www.rdocumentation.org/packages/base/topics/Extremes'>max(y)</a></code></p></td>
</tr> </tr>
<tr> <tr>
......
...@@ -32,7 +32,7 @@ ...@@ -32,7 +32,7 @@
<meta property="og:title" content="Single-split test — .test" /> <meta property="og:title" content="Single-split test — .test" />
<meta property="og:description" content="Compares models for a continuous response with a cutoff value." /> <meta property="og:description" content="Compares models for a continuous response with a cut-off value." />
<meta name="twitter:card" content="summary" /> <meta name="twitter:card" content="summary" />
...@@ -121,7 +121,7 @@ ...@@ -121,7 +121,7 @@
<div class="ref-description"> <div class="ref-description">
<p>Compares models for a continuous response with a cutoff value.</p> <p>Compares models for a continuous response with a cut-off value.</p>
</div> </div>
...@@ -137,7 +137,7 @@ vector of length \(n\)</p></td> ...@@ -137,7 +137,7 @@ vector of length \(n\)</p></td>
</tr> </tr>
<tr> <tr>
<th>cutoff</th> <th>cutoff</th>
<td><p>cutoff point for dichotomising outcome into classes<strong>:</strong> <td><p>cut-off point for dichotomising outcome into classes<strong>:</strong>
<em>meaningful</em> value between <code><a href='https://www.rdocumentation.org/packages/base/topics/Extremes'>min(y)</a></code> and <code><a href='https://www.rdocumentation.org/packages/base/topics/Extremes'>max(y)</a></code></p></td> <em>meaningful</em> value between <code><a href='https://www.rdocumentation.org/packages/base/topics/Extremes'>min(y)</a></code> and <code><a href='https://www.rdocumentation.org/packages/base/topics/Extremes'>max(y)</a></code></p></td>
</tr> </tr>
<tr> <tr>
......
...@@ -13,7 +13,7 @@ cornet(y, cutoff, X, alpha = 1, npi = 101, pi = NULL, nsigma = 99, ...@@ -13,7 +13,7 @@ cornet(y, cutoff, X, alpha = 1, npi = 101, pi = NULL, nsigma = 99,
\item{y}{continuous outcome\strong{:} \item{y}{continuous outcome\strong{:}
vector of length \eqn{n}} vector of length \eqn{n}}
\item{cutoff}{cutoff point for dichotomising outcome into classes\strong{:} \item{cutoff}{cut-off point for dichotomising outcome into classes\strong{:}
\emph{meaningful} value between \code{min(y)} and \code{max(y)}} \emph{meaningful} value between \code{min(y)} and \code{max(y)}}
\item{X}{features\strong{:} \item{X}{features\strong{:}
......
...@@ -11,7 +11,7 @@ ...@@ -11,7 +11,7 @@
\item{y}{continuous outcome\strong{:} \item{y}{continuous outcome\strong{:}
vector of length \eqn{n}} vector of length \eqn{n}}
\item{cutoff}{cutoff point for dichotomising outcome into classes\strong{:} \item{cutoff}{cut-off point for dichotomising outcome into classes\strong{:}
\emph{meaningful} value between \code{min(y)} and \code{max(y)}} \emph{meaningful} value between \code{min(y)} and \code{max(y)}}
\item{X}{features\strong{:} \item{X}{features\strong{:}
...@@ -31,7 +31,7 @@ or \code{NULL} (balance)} ...@@ -31,7 +31,7 @@ or \code{NULL} (balance)}
(linear regression uses the deviance)} (linear regression uses the deviance)}
} }
\description{ \description{
Compares models for a continuous response with a cutoff value. Compares models for a continuous response with a cut-off value.
} }
\details{ \details{
Uses k-fold cross-validation, Uses k-fold cross-validation,
......
...@@ -10,7 +10,7 @@ ...@@ -10,7 +10,7 @@
\item{y}{continuous outcome\strong{:} \item{y}{continuous outcome\strong{:}
vector of length \eqn{n}} vector of length \eqn{n}}
\item{cutoff}{cutoff point for dichotomising outcome into classes\strong{:} \item{cutoff}{cut-off point for dichotomising outcome into classes\strong{:}
\emph{meaningful} value between \code{min(y)} and \code{max(y)}} \emph{meaningful} value between \code{min(y)} and \code{max(y)}}
\item{X}{features\strong{:} \item{X}{features\strong{:}
...@@ -24,7 +24,7 @@ numeric between \eqn{0} (ridge) and \eqn{1} (lasso)} ...@@ -24,7 +24,7 @@ numeric between \eqn{0} (ridge) and \eqn{1} (lasso)}
(linear regression uses the deviance)} (linear regression uses the deviance)}
} }
\description{ \description{
Compares models for a continuous response with a cutoff value. Compares models for a continuous response with a cut-off value.
} }
\details{ \details{
Splits samples into 80% for training and 20% for testing, Splits samples into 80% for training and 20% for testing,
......
...@@ -56,6 +56,14 @@ testthat::test_that("predicted probabilities",{ # important! ...@@ -56,6 +56,14 @@ testthat::test_that("predicted probabilities",{ # important!
testthat::expect_true(all(a==b)) testthat::expect_true(all(a==b))
}) })
testthat::test_that("estimated coefficients",{ # important!
a <- cornet:::coef.cornet(fit)
b <- as.numeric(stats::coef(object=net$gaussian,s="lambda.min"))
c <- as.numeric(stats::coef(object=net$binomial,s="lambda.min"))
cond <- all(a[,"beta"]==b) & all(a[,"gamma"]==c)
testthat::expect_true(cond)
})
testthat::test_that("tuning parameters",{ testthat::test_that("tuning parameters",{
a <- (0 <= fit$sigma.min) & is.finite(fit$sigma.min) a <- (0 <= fit$sigma.min) & is.finite(fit$sigma.min)
b <- (0 <= fit$pi.min) & (fit$pi.min <= 1) b <- (0 <= fit$pi.min) & (fit$pi.min <= 1)
......
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