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joinet
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Armin Rauschenberger
joinet
Commits
15aecf6a
Commit
15aecf6a
authored
Nov 03, 2020
by
Armin Rauschenberger
Browse files
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vignette
parent
b9c0eead
Changes
11
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11 changed files
with
97 additions
and
42 deletions
+97
-42
CRAN-RELEASE
CRAN-RELEASE
+0
-2
R/functions.R
R/functions.R
+34
-13
docs/pkgdown.yml
docs/pkgdown.yml
+1
-1
docs/reference/coef.joinet.html
docs/reference/coef.joinet.html
+9
-3
docs/reference/predict.joinet.html
docs/reference/predict.joinet.html
+10
-5
docs/reference/weights.joinet.html
docs/reference/weights.joinet.html
+9
-5
man/coef.joinet.Rd
man/coef.joinet.Rd
+8
-2
man/cv.joinet.Rd
man/cv.joinet.Rd
+7
-2
man/joinet.Rd
man/joinet.Rd
+2
-5
man/predict.joinet.Rd
man/predict.joinet.Rd
+9
-2
man/weights.joinet.Rd
man/weights.joinet.Rd
+8
-2
No files found.
CRAN-RELEASE
deleted
100644 → 0
View file @
b9c0eead
This package was submitted to CRAN on 2020-10-21.
Once it is accepted, delete this file and tag the release (commit 8eb7bf5).
R/functions.R
View file @
15aecf6a
...
...
@@ -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
...
...
docs/pkgdown.yml
View file @
15aecf6a
...
...
@@ -4,5 +4,5 @@ pkgdown_sha: ~
articles
:
article
:
article.html
joinet
:
joinet.html
last_built
:
2020-11-03T08:
27
Z
last_built
:
2020-11-03T08:
45
Z
docs/reference/coef.joinet.html
View file @
15aecf6a
...
...
@@ -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'
>
<
-
</span>
<span
class=
'fl'
>
50
</span>
;
<span
class=
'no'
>
p
</span>
<span
class=
'kw'
>
<
-
</span>
<span
class=
'fl'
>
100
</span>
;
<span
class=
'no'
>
q
</span>
<span
class=
'kw'
>
<
-
</span>
<span
class=
'fl'
>
3
</span>
<span
class=
'no'
>
X
</span>
<span
class=
'kw'
>
<
-
</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'
>
<
-
</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'
>
<
-
</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'
>
<
-
</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'
>
<
-
</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'
>
<
-
</span>
<span
class=
'fl'
>
50
</span>
;
<span
class=
'no'
>
p
</span>
<span
class=
'kw'
>
<
-
</span>
<span
class=
'fl'
>
100
</span>
;
<span
class=
'no'
>
q
</span>
<span
class=
'kw'
>
<
-
</span>
<span
class=
'fl'
>
3
</span>
<span
class=
'no'
>
X
</span>
<span
class=
'kw'
>
<
-
</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'
>
<
-
</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'
>
<
-
</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'
>
<
-
</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"
>
...
...
docs/reference/predict.joinet.html
View file @
15aecf6a
...
...
@@ -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'
>
<
-
</span>
<span
class=
'fl'
>
50
</span>
;
<span
class=
'no'
>
p
</span>
<span
class=
'kw'
>
<
-
</span>
<span
class=
'fl'
>
100
</span>
;
<span
class=
'no'
>
q
</span>
<span
class=
'kw'
>
<
-
</span>
<span
class=
'fl'
>
3
</span>
<span
class=
'no'
>
X
</span>
<span
class=
'kw'
>
<
-
</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'
>
<
-
</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'
>
<
-
</span>
<span
class=
'fl'
>
1
</span>
*(
<span
class=
'no'
>
Y
</span>
[,
<span
class=
'fl'
>
1
</span>
]
<span
class=
'kw'
>
>
</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'
>
<
-
</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'
>
#
>
$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'
>
#
>
$base
#
>
[,1] [,2] [,3]
#
>
[1,] 0.41837245 -1.928585385 -2.49734037
#
>
[2,] 0.73430703 -1.232615541 -1.92258279
...
...
@@ -271,8 +271,13 @@ with \(n\) rows (samples) and \(q\) columns (variables).</p>
#
>
[48,] 0.07567690 -3.2214496 -3.11672913
#
>
[49,] 0.58299820 -0.1185430 -0.03693255
#
>
[50,] 0.42367190 -0.9519434 -1.64962005
#
>
</div><div
class=
'input'
>
</div></pre>
#
>
</div><div
class=
'input'
><span
class=
'kw'
>
if
</span>
(
<span
class=
'fl'
>
FALSE
</span>
) {
<span
class=
'no'
>
n
</span>
<span
class=
'kw'
>
<
-
</span>
<span
class=
'fl'
>
50
</span>
;
<span
class=
'no'
>
p
</span>
<span
class=
'kw'
>
<
-
</span>
<span
class=
'fl'
>
100
</span>
;
<span
class=
'no'
>
q
</span>
<span
class=
'kw'
>
<
-
</span>
<span
class=
'fl'
>
3
</span>
<span
class=
'no'
>
X
</span>
<span
class=
'kw'
>
<
-
</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'
>
<
-
</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'
>
<
-
</span>
<span
class=
'fl'
>
1
</span>
*(
<span
class=
'no'
>
Y
</span>
[,
<span
class=
'fl'
>
1
</span>
]
<span
class=
'kw'
>
>
</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'
>
<
-
</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"
>
...
...
docs/reference/weights.joinet.html
View file @
15aecf6a
...
...
@@ -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'
>
<
-
</span>
<span
class=
'fl'
>
50
</span>
;
<span
class=
'no'
>
p
</span>
<span
class=
'kw'
>
<
-
</span>
<span
class=
'fl'
>
100
</span>
;
<span
class=
'no'
>
q
</span>
<span
class=
'kw'
>
<
-
</span>
<span
class=
'fl'
>
3
</span>
<span
class=
'no'
>
X
</span>
<span
class=
'kw'
>
<
-
</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'
>
<
-
</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'
>
<
-
</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'
>
#
>
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'
>
#
>
y1 y2 y3
#
>
(Intercept) -0.04720442 -0.15165929 0.26901703
#
>
V1 0.00000000 0.01158793 0.65726908
#
>
V2 0.55230103 0.71134918 0.45932382
#
>
V3 0.60228936 0.49505561 0.01764908
</div><div
class=
'input'
>
</div></pre>
#
>
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'
>
<
-
</span>
<span
class=
'fl'
>
50
</span>
;
<span
class=
'no'
>
p
</span>
<span
class=
'kw'
>
<
-
</span>
<span
class=
'fl'
>
100
</span>
;
<span
class=
'no'
>
q
</span>
<span
class=
'kw'
>
<
-
</span>
<span
class=
'fl'
>
3
</span>
<span
class=
'no'
>
X
</span>
<span
class=
'kw'
>
<
-
</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'
>
<
-
</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'
>
<
-
</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
class=
"col-md-3 hidden-xs hidden-sm"
id=
"pkgdown-sidebar"
>
<nav
id=
"toc"
data-toggle=
"toc"
class=
"sticky-top"
>
...
...
man/coef.joinet.Rd
View file @
15aecf6a
...
...
@@ -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)}
}
man/cv.joinet.Rd
View file @
15aecf6a
...
...
@@ -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
...
...
man/joinet.Rd
View file @
15aecf6a
...
...
@@ -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}
...
...
man/predict.joinet.Rd
View file @
15aecf6a
...
...
@@ -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)}
}
man/weights.joinet.Rd
View file @
15aecf6a
...
...
@@ -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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