Skip to content
GitLab
Projects
Groups
Snippets
Help
Loading...
Help
Help
Support
Keyboard shortcuts
?
Submit feedback
Sign in
Toggle navigation
J
joinet
Project overview
Project overview
Details
Activity
Releases
Repository
Repository
Files
Commits
Branches
Tags
Contributors
Graph
Compare
Locked Files
Issues
0
Issues
0
List
Boards
Labels
Service Desk
Milestones
Merge Requests
0
Merge Requests
0
Requirements
Requirements
List
CI / CD
CI / CD
Pipelines
Jobs
Schedules
Security & Compliance
Security & Compliance
Dependency List
License Compliance
Operations
Operations
Environments
Packages & Registries
Packages & Registries
Package Registry
Container Registry
Analytics
Analytics
CI / CD
Code Review
Insights
Issue
Repository
Value Stream
Wiki
Wiki
External Wiki
External Wiki
Snippets
Snippets
Members
Members
Collapse sidebar
Close sidebar
Activity
Graph
Create a new issue
Jobs
Commits
Issue Boards
Open sidebar
Armin Rauschenberger
joinet
Commits
20ba57e5
Commit
20ba57e5
authored
Jun 29, 2020
by
Armin Rauschenberger
Browse files
Options
Browse Files
Download
Email Patches
Plain Diff
competing models
parent
476709d4
Changes
10
Expand all
Show whitespace changes
Inline
Side-by-side
Showing
10 changed files
with
295 additions
and
293 deletions
+295
-293
R/functions.R
R/functions.R
+232
-66
docs/articles/joinet.html
docs/articles/joinet.html
+1
-83
docs/pkgdown.yml
docs/pkgdown.yml
+1
-1
docs/reference/cv.joinet.html
docs/reference/cv.joinet.html
+1
-0
docs/reference/joinet.html
docs/reference/joinet.html
+1
-1
docs/reference/predict.joinet.html
docs/reference/predict.joinet.html
+51
-51
docs/reference/weights.joinet.html
docs/reference/weights.joinet.html
+5
-5
man/cv.joinet.Rd
man/cv.joinet.Rd
+1
-0
man/joinet.Rd
man/joinet.Rd
+1
-1
vignettes/joinet.Rmd
vignettes/joinet.Rmd
+1
-85
No files found.
R/functions.R
View file @
20ba57e5
This diff is collapsed.
Click to expand it.
docs/articles/joinet.html
View file @
20ba57e5
...
...
@@ -158,95 +158,13 @@
<div
class=
"sourceCode"
id=
"cb11"
><html><body><pre
class=
"r"
><span
class=
"fu"
><a
href=
"../reference/cv.joinet.html"
>
cv.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=
"no"
>
family
</span>
)
</pre></body></html></div>
<pre><code>
## [,1] [,2]
## base 1.204741 1.523550
## meta 1.1
61487 1.283678
## meta 1.1
85200 1.278125
## none 3.206394 3.495571
</code></pre>
</div>
<div
id=
"reference"
class=
"section level2"
>
<h2
class=
"hasAnchor"
>
<a
href=
"#reference"
class=
"anchor"
></a>
Reference
</h2>
<p>
Armin Rauschenberger and Enrico Glaab (2020). “joinet: predicting correlated outcomes jointly to improve clinical prognosis”.
<em>
Manuscript in preparation.
</em></p>
<!--
```r
#install.packages("MTPS")
data("HIV",package="MTPS")
loss1 <- cv.joinet(Y=YY,X=XX,mnorm=TRUE,spls=TRUE,mtps=TRUE)
#install.packages("spls")
data(yeast,package="spls")
loss2 <- cv.joinet(Y=yeast$y,X=yeast$x,mnorm=TRUE,spls=TRUE,mtps=TRUE)
data(mice,package="spls")
loss3 <- cv.joinet(Y=mice$y,X=mice$x,mnorm=TRUE,spls=TRUE,mtps=TRUE)
# install.packages("MRCE")
data(stock04,package="MRCE",verbose=TRUE)
# otherwise simulated
#install.packages("SiER")
# simulated!
library(MASS)
total.noise <- 0.1
rho <- 0.3
rho.e <- 0.2
nvar=500
nvarq <- 3
sigma2 <- total.noise/nvarq
sigmaX=0.1
nvar.eff=150
Sigma=matrix(0,nvar.eff,nvar.eff)
for(i in 1:nvar.eff){
for(j in 1:nvar.eff){
Sigma[i,j]=rho^(abs(i-j))
}
}
Sigma2.y <- matrix(sigma2*rho.e,nvarq, nvarq)
diag(Sigma2.y) <- sigma2
betas.true <- matrix(0, nvar, 3)
betas.true[1:15,1]=rep(1,15)/sqrt(15)
betas.true[16:45,2]=rep(0.5,30)/sqrt(30)
betas.true[46:105,3]=rep(0.25,60)/sqrt(60)
ntest <- 500
ntrain <- 90
ntot <- ntest+ntrain
X <- matrix(0,ntot,nvar)
X[,1:nvar.eff] <- mvrnorm(n=ntot, rep(0, nvar.eff), Sigma)
X[,-(1:nvar.eff)] <- matrix(sigmaX*rnorm((nvar-nvar.eff)*dim(X)[1]),
dim(X)[1],(nvar-nvar.eff))
Y <- X%*%betas.true
Y <- Y+mvrnorm(n=ntot, rep(0,nvarq), Sigma2.y)
fold <- rep(c(0,1),times=c(ntrain,ntest))
loss4 <- cv.joinet(Y=Y,X=X,foldid.ext=fold,mnorm=TRUE,spls=TRUE,mtps=TRUE)
#install.pacakges("GPM")
# simulated!
#install.packages("RMTL")
# simulated!
data <- RMTL::Create_simulated_data(Regularization="L21", #type="Regression")
#Y <- (do.call(what="cbind",args=data$Y)+1)/2
#X <- data$X[[1]] # example
#loss2 <- cv.joinet(Y=Y,X=X,mnorm=TRUE,spls=TRUE,mtps=TRUE)
```
-->
<!--
```r
#install.packages("plsgenomics")
data(Ecoli,package="plsgenomics")
X <- Ecoli$CONNECdata
Y <- Ecoli$GEdata
loss2 <- cv.joinet(Y=Y,X=X,mnorm=TRUE,mtps=TRUE)
#install.packages("BiocManager")
#BiocManager::install("mixOmics")
data(liver.toxicity,package="mixOmics")
X <- as.matrix(liver.toxicity$gene)
Y <- as.matrix(liver.toxicity$clinic)
Y[,"Cholesterol.mg.dL."] <- -Y[,"Cholesterol.mg.dL."]
loss3 <- cv.joinet(Y=Y,X=X,mnorm=TRUE,mtps=TRUE)
```
-->
</div>
</div>
...
...
docs/pkgdown.yml
View file @
20ba57e5
...
...
@@ -4,5 +4,5 @@ pkgdown_sha: ~
articles
:
article
:
article.html
joinet
:
joinet.html
last_built
:
2020-06-
08T15:55
Z
last_built
:
2020-06-
29T15:24
Z
docs/reference/cv.joinet.html
View file @
20ba57e5
...
...
@@ -140,6 +140,7 @@
<span
class=
'kw'
>
compare
</span>
<span
class=
'kw'
>
=
</span>
<span
class=
'kw'
>
NULL
</span>
,
<span
class=
'kw'
>
mice
</span>
<span
class=
'kw'
>
=
</span>
<span
class=
'fl'
>
FALSE
</span>
,
<span
class=
'kw'
>
cvpred
</span>
<span
class=
'kw'
>
=
</span>
<span
class=
'fl'
>
FALSE
</span>
,
<span
class=
'kw'
>
times
</span>
<span
class=
'kw'
>
=
</span>
<span
class=
'fl'
>
FALSE
</span>
,
<span
class=
'no'
>
...
</span>
)
</pre>
...
...
docs/reference/joinet.html
View file @
20ba57e5
...
...
@@ -134,7 +134,7 @@
<span
class=
'kw'
>
foldid
</span>
<span
class=
'kw'
>
=
</span>
<span
class=
'kw'
>
NULL
</span>
,
<span
class=
'kw'
>
type.measure
</span>
<span
class=
'kw'
>
=
</span>
<span
class=
'st'
>
"deviance"
</span>
,
<span
class=
'kw'
>
alpha.base
</span>
<span
class=
'kw'
>
=
</span>
<span
class=
'fl'
>
1
</span>
,
<span
class=
'kw'
>
alpha.meta
</span>
<span
class=
'kw'
>
=
</span>
<span
class=
'fl'
>
0
</span>
,
<span
class=
'kw'
>
alpha.meta
</span>
<span
class=
'kw'
>
=
</span>
<span
class=
'fl'
>
1
</span>
,
<span
class=
'no'
>
...
</span>
)
</pre>
...
...
docs/reference/predict.joinet.html
View file @
20ba57e5
...
...
@@ -219,56 +219,56 @@ with \(n\) rows (samples) and \(q\) columns (variables).</p>
#
>
#
>
$meta
#
>
[,1] [,2] [,3]
#
>
[1,] 0.1
20026857 -2.63552370 -2.58637745
#
>
[2,] 0.
311517089 -1.57742790 -1.80530334
#
>
[3,] 0.9
70038575 2.83530787 2.50770389
#
>
[4,] 0.98
8790465 3.94203727 3.41749124
#
>
[5,] 0.
702397389 0.20191699 -0.07301232
#
>
[6,] 0.0
69874337 -3.01383050 -2.75113316
#
>
[7,] 0.
178293600 -1.79055373 -1.33607264
#
>
[8,] 0.99
4417547 4.65204823 4.42063500
#
>
[9,] 0.8254
54272 0.92712611 0.33068070
#
>
[10,] 0.1
22295626 -2.58218395 -2.83894610
#
>
[11,] 0.9
92972765 4.45732386 4.34260769
#
>
[12,] 0.
315048704 -0.99259865 -0.55695917
#
>
[13,] 0.0
06376865 -5.52584767 -5.43421552
#
>
[14,] 0.6
04946394 0.15758601 0.59296195
#
>
[15,] 0.
356113893 -0.95306415 -0.75195663
#
>
[16,] 0.4
96057561 -0.75220207 -1.2697836
0
#
>
[17,] 0.
320794509 -1.10958000 -1.05497247
#
>
[18,] 0.
804808814 0.64766735 0.02552338
#
>
[19,] 0.8
34600977 1.22772641 1.64662
367
#
>
[20,] 0.06
2637571 -3.37591257 -3.52530885
#
>
[21,] 0.2
71715919 -1.32688363 -0.85251362
#
>
[22,] 0.
507637975 -0.60258988 -0.83624877
#
>
[23,] 0.
694579538 0.19562106 -0.51989858
#
>
[24,] 0.
406609311 -0.57645076 -0.18326513
#
>
[25,] 0.01
2589218 -4.82289140 -4.55079851
#
>
[26,] 0.93
5270035 2.28086412 2.23449684
#
>
[27,] 0.1
43615352 -2.33101536 -2.18288391
#
>
[28,] 0.9
71697981 2.86526752 2.61585773
#
>
[29,] 0.0
13944811 -4.69966856 -4.55513448
#
>
[30,] 0.0157
68781 -4.71928228 -4.44410746
#
>
[31,] 0.8
91631228 1.50966480 1.39712353
#
>
[32,] 0.85
3434630 1.11696980 0.44705866
#
>
[33,] 0.7
72218415 0.74754148 0.52945800
#
>
[34,] 0.
480168883 -0.47818857 -0.27919160
#
>
[35,] 0.0
30260125 -4.02999089 -3.72147791
#
>
[36,] 0.94
6608961 2.36236767 2.06071075
#
>
[37,] 0.1
31953701 -2.45489591 -2.16067825
#
>
[38,] 0.1
42539577 -2.28403264 -1.8568289
7
#
>
[39,] 0.98
5751175 3.60577123 2.9609010
3
#
>
[40,] 0.8
63879903 1.29591149 0.94749069
#
>
[41,] 0.2
04237405 -1.70922989 -1.59867884
#
>
[42,] 0.8
52342486 1.15387209 0.99870566
#
>
[43,] 0.5
59959816 -0.35427152 -0.43712903
#
>
[44,] 0.1
70830538 -2.18882713 -1.8150207
9
#
>
[45,] 0.6
39682562 -0.00439300 -0.15009278
#
>
[46,] 0.9
34408843 2.02660474 1.83111336
#
>
[47,] 0.3
58655524 -1.10381588 -0.90429501
#
>
[48,] 0.07
0055480 -3.13250260 -3.05061558
#
>
[49,] 0.
681260321 0.05548031 -0.11998977
#
>
[50,] 0.
317122867 -1.19819266 -1.48472862
#
>
[1,] 0.1
0220137 -2.8366810 -2.58549073
#
>
[2,] 0.
22806673 -1.8261107 -1.76560859
#
>
[3,] 0.9
5484141 2.8130533 2.62981542
#
>
[4,] 0.98
730517 4.1550932 3.46554651
#
>
[5,] 0.
64845882 0.1406465 -0.04254334
#
>
[6,] 0.0
8701080 -3.0352129 -2.82347419
#
>
[7,] 0.
24075871 -1.6987418 -1.38562725
#
>
[8,] 0.99
171832 4.7229217 4.59039026
#
>
[9,] 0.8254
0857 1.0679076 0.27264687
#
>
[10,] 0.1
3617019 -2.5849863 -2.95244727
#
>
[11,] 0.9
8981676 4.5178102 4.52008410
#
>
[12,] 0.
41469313 -0.8318596 -0.60385413
#
>
[13,] 0.0
1027685 -5.5214546 -5.64340291
#
>
[14,] 0.6
4930175 0.2459392 0.62723142
#
>
[15,] 0.
41386111 -0.8637077 -0.78947614
#
>
[16,] 0.4
5380923 -0.7919286 -1.3141001
0
#
>
[17,] 0.
40677141 -0.9432038 -1.14733110
#
>
[18,] 0.
75190956 0.6145579 0.02843515
#
>
[19,] 0.8
0419429 1.1601342 1.79330
367
#
>
[20,] 0.06
109382 -3.5090532 -3.60577442
#
>
[21,] 0.2
9707148 -1.3498797 -0.83013621
#
>
[22,] 0.
47255039 -0.6514714 -0.84183516
#
>
[23,] 0.
72776624 0.4000683 -0.64909323
#
>
[24,] 0.
52225525 -0.3720559 -0.23537421
#
>
[25,] 0.01
722845 -4.8908178 -4.68018275
#
>
[26,] 0.93
788800 2.4494650 2.27769155
#
>
[27,] 0.1
3861339 -2.4543910 -2.19278248
#
>
[28,] 0.9
5152342 2.7650921 2.78092452
#
>
[29,] 0.0
2171825 -4.6769505 -4.73129956
#
>
[30,] 0.0157
0247 -4.9537324 -4.49632044
#
>
[31,] 0.8
5305109 1.4396438 1.50410997
#
>
[32,] 0.85
232458 1.2707274 0.38427369
#
>
[33,] 0.7
9166183 0.8978043 0.49722869
#
>
[34,] 0.
50644688 -0.4392424 -0.27447864
#
>
[35,] 0.0
2911065 -4.2534806 -3.74533419
#
>
[36,] 0.94
251258 2.4986830 2.09603282
#
>
[37,] 0.1
1040807 -2.6864056 -2.11437644
#
>
[38,] 0.1
2885189 -2.4765109 -1.8068593
7
#
>
[39,] 0.98
204701 3.7581482 3.0088087
3
#
>
[40,] 0.8
5949146 1.4074652 0.94281190
#
>
[41,] 0.2
7978357 -1.5562501 -1.70556618
#
>
[42,] 0.8
1267168 1.1047951 1.07696011
#
>
[43,] 0.5
1433013 -0.4308933 -0.40489984
#
>
[44,] 0.1
2318913 -2.5118215 -1.7095211
9
#
>
[45,] 0.6
0957965 -0.0276023 -0.13221472
#
>
[46,] 0.9
0379982 1.9552732 1.95275535
#
>
[47,] 0.3
2662397 -1.2267246 -0.85622205
#
>
[48,] 0.07
567690 -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>
...
...
docs/reference/weights.joinet.html
View file @
20ba57e5
...
...
@@ -159,10 +159,10 @@ in the row on the outcomes in the column.</p>
<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
#
>
(Intercept) -0.0
2352901 -0.1279338 0.1990621
#
>
V1 0.
10704102 0.2456441 0.4650750
#
>
V2 0.
48427425 0.5331528 0.389435
2
#
>
V3 0.
52435963 0.4199606 0.2731577
</div><div
class=
'input'
>
#
>
(Intercept) -0.0
4720442 -0.15165929 0.26901703
#
>
V1 0.
00000000 0.01158793 0.65726908
#
>
V2 0.
55230103 0.71134918 0.4593238
2
#
>
V3 0.
60228936 0.49505561 0.01764908
</div><div
class=
'input'
>
</div></pre>
</div>
<div
class=
"col-md-3 hidden-xs hidden-sm"
id=
"pkgdown-sidebar"
>
...
...
man/cv.joinet.Rd
View file @
20ba57e5
...
...
@@ -18,6 +18,7 @@ cv.joinet(
compare = NULL,
mice = FALSE,
cvpred = FALSE,
times = FALSE,
...
)
}
...
...
man/joinet.Rd
View file @
20ba57e5
...
...
@@ -12,7 +12,7 @@ joinet(
foldid = NULL,
type.measure = "deviance",
alpha.base = 1,
alpha.meta =
0
,
alpha.meta =
1
,
...
)
}
...
...
vignettes/joinet.Rmd
View file @
20ba57e5
...
...
@@ -124,87 +124,3 @@ cv.joinet(Y=Y,X=X,family=family)
## Reference
Armin Rauschenberger and Enrico Glaab (2020). "joinet: predicting correlated outcomes jointly to improve clinical prognosis". *Manuscript in preparation.*
<!--
```{r,eval=FALSE}
#install.packages("MTPS")
data("HIV",package="MTPS")
loss1 <- cv.joinet(Y=YY,X=XX,mnorm=TRUE,spls=TRUE,mtps=TRUE)
#install.packages("spls")
data(yeast,package="spls")
loss2 <- cv.joinet(Y=yeast$y,X=yeast$x,mnorm=TRUE,spls=TRUE,mtps=TRUE)
data(mice,package="spls")
loss3 <- cv.joinet(Y=mice$y,X=mice$x,mnorm=TRUE,spls=TRUE,mtps=TRUE)
# install.packages("MRCE")
data(stock04,package="MRCE",verbose=TRUE)
# otherwise simulated
#install.packages("SiER")
# simulated!
library(MASS)
total.noise <- 0.1
rho <- 0.3
rho.e <- 0.2
nvar=500
nvarq <- 3
sigma2 <- total.noise/nvarq
sigmaX=0.1
nvar.eff=150
Sigma=matrix(0,nvar.eff,nvar.eff)
for(i in 1:nvar.eff){
for(j in 1:nvar.eff){
Sigma[i,j]=rho^(abs(i-j))
}
}
Sigma2.y <- matrix(sigma2*rho.e,nvarq, nvarq)
diag(Sigma2.y) <- sigma2
betas.true <- matrix(0, nvar, 3)
betas.true[1:15,1]=rep(1,15)/sqrt(15)
betas.true[16:45,2]=rep(0.5,30)/sqrt(30)
betas.true[46:105,3]=rep(0.25,60)/sqrt(60)
ntest <- 500
ntrain <- 90
ntot <- ntest+ntrain
X <- matrix(0,ntot,nvar)
X[,1:nvar.eff] <- mvrnorm(n=ntot, rep(0, nvar.eff), Sigma)
X[,-(1:nvar.eff)] <- matrix(sigmaX*rnorm((nvar-nvar.eff)*dim(X)[1]),
dim(X)[1],(nvar-nvar.eff))
Y <- X%*%betas.true
Y <- Y+mvrnorm(n=ntot, rep(0,nvarq), Sigma2.y)
fold <- rep(c(0,1),times=c(ntrain,ntest))
loss4 <- cv.joinet(Y=Y,X=X,foldid.ext=fold,mnorm=TRUE,spls=TRUE,mtps=TRUE)
#install.pacakges("GPM")
# simulated!
#install.packages("RMTL")
# simulated!
data <- RMTL::Create_simulated_data(Regularization="L21", #type="Regression")
#Y <- (do.call(what="cbind",args=data$Y)+1)/2
#X <- data$X[[1]] # example
#loss2 <- cv.joinet(Y=Y,X=X,mnorm=TRUE,spls=TRUE,mtps=TRUE)
```
-->
<!--
```{r,eval=FALSE}
#install.packages("plsgenomics")
data(Ecoli,package="plsgenomics")
X <- Ecoli$CONNECdata
Y <- Ecoli$GEdata
loss2 <- cv.joinet(Y=Y,X=X,mnorm=TRUE,mtps=TRUE)
#install.packages("BiocManager")
#BiocManager::install("mixOmics")
data(liver.toxicity,package="mixOmics")
X <- as.matrix(liver.toxicity$gene)
Y <- as.matrix(liver.toxicity$clinic)
Y[,"Cholesterol.mg.dL."] <- -Y[,"Cholesterol.mg.dL."]
loss3 <- cv.joinet(Y=Y,X=X,mnorm=TRUE,mtps=TRUE)
```
-->
Write
Preview
Markdown
is supported
0%
Try again
or
attach a new file
Attach a file
Cancel
You are about to add
0
people
to the discussion. Proceed with caution.
Finish editing this message first!
Cancel
Please
register
or
sign in
to comment