Last updated on 2020-02-19 10:49:01 CET.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 1.7.1 | 11.01 | 82.93 | 93.94 | ERROR | |
| r-devel-linux-x86_64-debian-gcc | 1.7.1 | 7.99 | 62.00 | 69.99 | ERROR | |
| r-devel-linux-x86_64-fedora-clang | 1.7.1 | 110.84 | ERROR | |||
| r-devel-linux-x86_64-fedora-gcc | 1.7.1 | 107.13 | ERROR | |||
| r-devel-windows-ix86+x86_64 | 1.7.1 | 19.00 | 88.00 | 107.00 | OK | |
| r-devel-windows-ix86+x86_64-gcc8 | 1.7.1 | 27.00 | 125.00 | 152.00 | OK | |
| r-patched-linux-x86_64 | 1.7.1 | 7.92 | 74.11 | 82.03 | OK | |
| r-patched-solaris-x86 | 1.7.1 | 154.50 | OK | |||
| r-release-linux-x86_64 | 1.7.1 | 8.96 | 74.29 | 83.25 | OK | |
| r-release-windows-ix86+x86_64 | 1.7.1 | 18.00 | 85.00 | 103.00 | OK | |
| r-release-osx-x86_64 | 1.7.1 | OK | ||||
| r-oldrel-windows-ix86+x86_64 | 1.7.1 | 11.00 | 85.00 | 96.00 | OK | |
| r-oldrel-osx-x86_64 | 1.7.1 | OK |
Version: 1.7.1
Check: examples
Result: ERROR
Running examples in 'orderedLasso-Ex.R' failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: orderedLasso.cv
> ### Title: Cross-validation function for the ordered lasso
> ### Aliases: orderedLasso.cv
>
> ### ** Examples
>
> set.seed(3)
> n = 50
> b = c(4,3,1,0)
> p = length(b)
> x = matrix(rnorm(n*p),nrow = n)
> sigma = 5
> y = x %*% b + sigma * rnorm(n, 0, 1)
> cvmodel = orderedLasso.cv(x,y, intercept = FALSE, trace = TRUE,
+ method = "Solve.QP", strongly.ordered = TRUE)
Fold 1 :
lambda= 0.0555431880114968
lambda= 0.0648632585178277
lambda= 0.0757472240282587
lambda= 0.0884575039721481
lambda= 0.103300551397943
lambda= 0.120634241753858
lambda= 0.14087650149579
lambda= 0.164515384563759
lambda= 0.192120839677229
lambda= 0.22435845216639
lambda= 0.26200549166382
lambda= 0.305969652576716
lambda= 0.357310939184576
lambda= 0.417267223026156
lambda= 0.487284088780777
lambda= 0.569049688247448
lambda= 0.664535442773709
lambda= 0.776043575496029
lambda= 0.906262619424709
lambda= 1.05833223970905
lambda= 1.23591893298942
lambda= 1.44330442899635
lambda= 1.6854889258164
lambda= 1.96831164789345
lambda= 2.29859163349676
lambda= 2.68429214613239
lambda= 3.1347126739632
lambda= 3.6607131464672
lambda= 4.27497577434272
lambda= 4.99231082578924
lambda= 5.83001371162726
lambda= 6.80828198880995
lambda= 7.9507023365501
lambda= 9.28481924637094
lambda= 10.8427991375648
lambda= 12.662205910312
lambda= 14.7869066355452
lambda= 17.2681292183268
lambda= 20.165697535686
lambda= 23.5494738288839
lambda= 27.5010431271164
lambda= 32.1156803151964
lambda= 37.5046472724847
lambda= 43.7978754685737
lambda= 51.1470986948335
lambda= 59.7295114640004
lambda= 69.752041284182
lambda= 81.4563378145596
lambda= 95.124599194552
lambda= 111.086376022994
----------- FAILURE REPORT --------------
--- failure: the condition has length > 1 ---
--- srcref ---
:
--- package (from environment) ---
orderedLasso
--- call from context ---
predict.orderedLasso(object = object, newdata = newdata, ...)
--- call from argument ---
if (class(object$beta) == "numeric") {
if (is.null(object$b0)) {
b0 = 0
if (ordered)
b0.ordered = 0
}
else {
b0 = object$b0
if (ordered)
b0.ordered = object$b0.ordered
}
yhat = as.vector(newdata %*% object$beta + b0)
if (ordered)
yhat.ordered = as.vector(newdata %*% object$beta.ordered +
b0.ordered)
} else {
if (is.null(object$b0)) {
b0 = rep(0, length = ncol(object$beta))
if (ordered)
b0.ordered = rep(0, length = ncol(object$beta))
}
else {
b0 = object$b0
if (ordered)
b0.ordered = object$b0.ordered
}
nlam = ncol(object$beta)
yhat = matrix(NA, n, nlam)
if (ordered)
yhat.ordered = matrix(NA, n, nlam)
for (i in seq(nlam)) {
yhat[, i] = as.vector(newdata %*% object$beta[, i] +
b0[i])
if (ordered)
yhat.ordered[, i] = as.vector(newdata %*% object$beta.ordered[,
i] + b0.ordered[i])
}
}
--- R stacktrace ---
where 1: predict.orderedLasso(object = object, newdata = newdata, ...)
where 2: predict.orderedLasso.path(a, newdata = x[folds[[ii]], ])
where 3: orderedLasso.cv(x, y, intercept = FALSE, trace = TRUE, method = "Solve.QP",
strongly.ordered = TRUE)
--- value of length: 2 type: logical ---
[1] FALSE FALSE
--- function from context ---
function (object, newdata, ...)
{
n <- nrow(newdata)
ordered = object$strongly.ordered
if (class(object$beta) == "numeric") {
if (is.null(object$b0)) {
b0 = 0
if (ordered)
b0.ordered = 0
}
else {
b0 = object$b0
if (ordered)
b0.ordered = object$b0.ordered
}
yhat = as.vector(newdata %*% object$beta + b0)
if (ordered)
yhat.ordered = as.vector(newdata %*% object$beta.ordered +
b0.ordered)
}
else {
if (is.null(object$b0)) {
b0 = rep(0, length = ncol(object$beta))
if (ordered)
b0.ordered = rep(0, length = ncol(object$beta))
}
else {
b0 = object$b0
if (ordered)
b0.ordered = object$b0.ordered
}
nlam = ncol(object$beta)
yhat = matrix(NA, n, nlam)
if (ordered)
yhat.ordered = matrix(NA, n, nlam)
for (i in seq(nlam)) {
yhat[, i] = as.vector(newdata %*% object$beta[, i] +
b0[i])
if (ordered)
yhat.ordered[, i] = as.vector(newdata %*% object$beta.ordered[,
i] + b0.ordered[i])
}
}
if (!ordered)
yhat.ordered = NULL
return(list(yhat = yhat, yhat.ordered = yhat.ordered))
}
<bytecode: 0x6aaab58>
<environment: namespace:orderedLasso>
--- function search by body ---
Function predict.orderedLasso in namespace orderedLasso has this body.
----------- END OF FAILURE REPORT --------------
Error in if (class(object$beta) == "numeric") { :
the condition has length > 1
Calls: orderedLasso.cv -> predict.orderedLasso.path -> predict.orderedLasso
Execution halted
Flavor: r-devel-linux-x86_64-debian-clang
Version: 1.7.1
Check: examples
Result: ERROR
Running examples in ‘orderedLasso-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: orderedLasso.cv
> ### Title: Cross-validation function for the ordered lasso
> ### Aliases: orderedLasso.cv
>
> ### ** Examples
>
> set.seed(3)
> n = 50
> b = c(4,3,1,0)
> p = length(b)
> x = matrix(rnorm(n*p),nrow = n)
> sigma = 5
> y = x %*% b + sigma * rnorm(n, 0, 1)
> cvmodel = orderedLasso.cv(x,y, intercept = FALSE, trace = TRUE,
+ method = "Solve.QP", strongly.ordered = TRUE)
Fold 1 :
lambda= 0.0555431880114968
lambda= 0.0648632585178277
lambda= 0.0757472240282587
lambda= 0.0884575039721481
lambda= 0.103300551397943
lambda= 0.120634241753858
lambda= 0.14087650149579
lambda= 0.164515384563759
lambda= 0.192120839677229
lambda= 0.22435845216639
lambda= 0.26200549166382
lambda= 0.305969652576716
lambda= 0.357310939184576
lambda= 0.417267223026156
lambda= 0.487284088780777
lambda= 0.569049688247448
lambda= 0.664535442773709
lambda= 0.776043575496029
lambda= 0.906262619424709
lambda= 1.05833223970905
lambda= 1.23591893298942
lambda= 1.44330442899635
lambda= 1.6854889258164
lambda= 1.96831164789345
lambda= 2.29859163349676
lambda= 2.68429214613239
lambda= 3.1347126739632
lambda= 3.6607131464672
lambda= 4.27497577434272
lambda= 4.99231082578924
lambda= 5.83001371162726
lambda= 6.80828198880995
lambda= 7.9507023365501
lambda= 9.28481924637094
lambda= 10.8427991375648
lambda= 12.662205910312
lambda= 14.7869066355452
lambda= 17.2681292183268
lambda= 20.165697535686
lambda= 23.5494738288839
lambda= 27.5010431271164
lambda= 32.1156803151964
lambda= 37.5046472724847
lambda= 43.7978754685737
lambda= 51.1470986948335
lambda= 59.7295114640004
lambda= 69.752041284182
lambda= 81.4563378145596
lambda= 95.124599194552
lambda= 111.086376022994
----------- FAILURE REPORT --------------
--- failure: the condition has length > 1 ---
--- srcref ---
:
--- package (from environment) ---
orderedLasso
--- call from context ---
predict.orderedLasso(object = object, newdata = newdata, ...)
--- call from argument ---
if (class(object$beta) == "numeric") {
if (is.null(object$b0)) {
b0 = 0
if (ordered)
b0.ordered = 0
}
else {
b0 = object$b0
if (ordered)
b0.ordered = object$b0.ordered
}
yhat = as.vector(newdata %*% object$beta + b0)
if (ordered)
yhat.ordered = as.vector(newdata %*% object$beta.ordered +
b0.ordered)
} else {
if (is.null(object$b0)) {
b0 = rep(0, length = ncol(object$beta))
if (ordered)
b0.ordered = rep(0, length = ncol(object$beta))
}
else {
b0 = object$b0
if (ordered)
b0.ordered = object$b0.ordered
}
nlam = ncol(object$beta)
yhat = matrix(NA, n, nlam)
if (ordered)
yhat.ordered = matrix(NA, n, nlam)
for (i in seq(nlam)) {
yhat[, i] = as.vector(newdata %*% object$beta[, i] +
b0[i])
if (ordered)
yhat.ordered[, i] = as.vector(newdata %*% object$beta.ordered[,
i] + b0.ordered[i])
}
}
--- R stacktrace ---
where 1: predict.orderedLasso(object = object, newdata = newdata, ...)
where 2: predict.orderedLasso.path(a, newdata = x[folds[[ii]], ])
where 3: orderedLasso.cv(x, y, intercept = FALSE, trace = TRUE, method = "Solve.QP",
strongly.ordered = TRUE)
--- value of length: 2 type: logical ---
[1] FALSE FALSE
--- function from context ---
function (object, newdata, ...)
{
n <- nrow(newdata)
ordered = object$strongly.ordered
if (class(object$beta) == "numeric") {
if (is.null(object$b0)) {
b0 = 0
if (ordered)
b0.ordered = 0
}
else {
b0 = object$b0
if (ordered)
b0.ordered = object$b0.ordered
}
yhat = as.vector(newdata %*% object$beta + b0)
if (ordered)
yhat.ordered = as.vector(newdata %*% object$beta.ordered +
b0.ordered)
}
else {
if (is.null(object$b0)) {
b0 = rep(0, length = ncol(object$beta))
if (ordered)
b0.ordered = rep(0, length = ncol(object$beta))
}
else {
b0 = object$b0
if (ordered)
b0.ordered = object$b0.ordered
}
nlam = ncol(object$beta)
yhat = matrix(NA, n, nlam)
if (ordered)
yhat.ordered = matrix(NA, n, nlam)
for (i in seq(nlam)) {
yhat[, i] = as.vector(newdata %*% object$beta[, i] +
b0[i])
if (ordered)
yhat.ordered[, i] = as.vector(newdata %*% object$beta.ordered[,
i] + b0.ordered[i])
}
}
if (!ordered)
yhat.ordered = NULL
return(list(yhat = yhat, yhat.ordered = yhat.ordered))
}
<bytecode: 0x55f5a98aceb0>
<environment: namespace:orderedLasso>
--- function search by body ---
Function predict.orderedLasso in namespace orderedLasso has this body.
----------- END OF FAILURE REPORT --------------
Error in if (class(object$beta) == "numeric") { :
the condition has length > 1
Calls: orderedLasso.cv -> predict.orderedLasso.path -> predict.orderedLasso
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 1.7.1
Check: examples
Result: ERROR
Running examples in ‘orderedLasso-Ex.R’ failed
The error most likely occurred in:
> ### Name: orderedLasso.cv
> ### Title: Cross-validation function for the ordered lasso
> ### Aliases: orderedLasso.cv
>
> ### ** Examples
>
> set.seed(3)
> n = 50
> b = c(4,3,1,0)
> p = length(b)
> x = matrix(rnorm(n*p),nrow = n)
> sigma = 5
> y = x %*% b + sigma * rnorm(n, 0, 1)
> cvmodel = orderedLasso.cv(x,y, intercept = FALSE, trace = TRUE,
+ method = "Solve.QP", strongly.ordered = TRUE)
Fold 1 :
lambda= 0.0555431880114968
lambda= 0.0648632585178277
lambda= 0.0757472240282587
lambda= 0.0884575039721481
lambda= 0.103300551397943
lambda= 0.120634241753858
lambda= 0.14087650149579
lambda= 0.164515384563759
lambda= 0.192120839677229
lambda= 0.22435845216639
lambda= 0.26200549166382
lambda= 0.305969652576716
lambda= 0.357310939184576
lambda= 0.417267223026156
lambda= 0.487284088780777
lambda= 0.569049688247448
lambda= 0.664535442773709
lambda= 0.776043575496029
lambda= 0.906262619424709
lambda= 1.05833223970905
lambda= 1.23591893298942
lambda= 1.44330442899635
lambda= 1.6854889258164
lambda= 1.96831164789345
lambda= 2.29859163349676
lambda= 2.68429214613239
lambda= 3.1347126739632
lambda= 3.6607131464672
lambda= 4.27497577434272
lambda= 4.99231082578924
lambda= 5.83001371162726
lambda= 6.80828198880995
lambda= 7.9507023365501
lambda= 9.28481924637094
lambda= 10.8427991375648
lambda= 12.662205910312
lambda= 14.7869066355452
lambda= 17.2681292183268
lambda= 20.165697535686
lambda= 23.5494738288839
lambda= 27.5010431271164
lambda= 32.1156803151964
lambda= 37.5046472724847
lambda= 43.7978754685737
lambda= 51.1470986948335
lambda= 59.7295114640004
lambda= 69.752041284182
lambda= 81.4563378145596
lambda= 95.124599194552
lambda= 111.086376022994
----------- FAILURE REPORT --------------
--- failure: the condition has length > 1 ---
--- srcref ---
:
--- package (from environment) ---
orderedLasso
--- call from context ---
predict.orderedLasso(object = object, newdata = newdata, ...)
--- call from argument ---
if (class(object$beta) == "numeric") {
if (is.null(object$b0)) {
b0 = 0
if (ordered)
b0.ordered = 0
}
else {
b0 = object$b0
if (ordered)
b0.ordered = object$b0.ordered
}
yhat = as.vector(newdata %*% object$beta + b0)
if (ordered)
yhat.ordered = as.vector(newdata %*% object$beta.ordered +
b0.ordered)
} else {
if (is.null(object$b0)) {
b0 = rep(0, length = ncol(object$beta))
if (ordered)
b0.ordered = rep(0, length = ncol(object$beta))
}
else {
b0 = object$b0
if (ordered)
b0.ordered = object$b0.ordered
}
nlam = ncol(object$beta)
yhat = matrix(NA, n, nlam)
if (ordered)
yhat.ordered = matrix(NA, n, nlam)
for (i in seq(nlam)) {
yhat[, i] = as.vector(newdata %*% object$beta[, i] +
b0[i])
if (ordered)
yhat.ordered[, i] = as.vector(newdata %*% object$beta.ordered[,
i] + b0.ordered[i])
}
}
--- R stacktrace ---
where 1: predict.orderedLasso(object = object, newdata = newdata, ...)
where 2: predict.orderedLasso.path(a, newdata = x[folds[[ii]], ])
where 3: orderedLasso.cv(x, y, intercept = FALSE, trace = TRUE, method = "Solve.QP",
strongly.ordered = TRUE)
--- value of length: 2 type: logical ---
[1] FALSE FALSE
--- function from context ---
function (object, newdata, ...)
{
n <- nrow(newdata)
ordered = object$strongly.ordered
if (class(object$beta) == "numeric") {
if (is.null(object$b0)) {
b0 = 0
if (ordered)
b0.ordered = 0
}
else {
b0 = object$b0
if (ordered)
b0.ordered = object$b0.ordered
}
yhat = as.vector(newdata %*% object$beta + b0)
if (ordered)
yhat.ordered = as.vector(newdata %*% object$beta.ordered +
b0.ordered)
}
else {
if (is.null(object$b0)) {
b0 = rep(0, length = ncol(object$beta))
if (ordered)
b0.ordered = rep(0, length = ncol(object$beta))
}
else {
b0 = object$b0
if (ordered)
b0.ordered = object$b0.ordered
}
nlam = ncol(object$beta)
yhat = matrix(NA, n, nlam)
if (ordered)
yhat.ordered = matrix(NA, n, nlam)
for (i in seq(nlam)) {
yhat[, i] = as.vector(newdata %*% object$beta[, i] +
b0[i])
if (ordered)
yhat.ordered[, i] = as.vector(newdata %*% object$beta.ordered[,
i] + b0.ordered[i])
}
}
if (!ordered)
yhat.ordered = NULL
return(list(yhat = yhat, yhat.ordered = yhat.ordered))
}
<bytecode: 0x4e1c9b0>
<environment: namespace:orderedLasso>
--- function search by body ---
Function predict.orderedLasso in namespace orderedLasso has this body.
----------- END OF FAILURE REPORT --------------
Error in if (class(object$beta) == "numeric") { :
the condition has length > 1
Calls: orderedLasso.cv -> predict.orderedLasso.path -> predict.orderedLasso
Execution halted
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 1.7.1
Check: examples
Result: ERROR
Running examples in ‘orderedLasso-Ex.R’ failed
The error most likely occurred in:
> ### Name: orderedLasso.cv
> ### Title: Cross-validation function for the ordered lasso
> ### Aliases: orderedLasso.cv
>
> ### ** Examples
>
> set.seed(3)
> n = 50
> b = c(4,3,1,0)
> p = length(b)
> x = matrix(rnorm(n*p),nrow = n)
> sigma = 5
> y = x %*% b + sigma * rnorm(n, 0, 1)
> cvmodel = orderedLasso.cv(x,y, intercept = FALSE, trace = TRUE,
+ method = "Solve.QP", strongly.ordered = TRUE)
Fold 1 :
lambda= 0.0555431880114968
lambda= 0.0648632585178277
lambda= 0.0757472240282587
lambda= 0.0884575039721481
lambda= 0.103300551397943
lambda= 0.120634241753858
lambda= 0.14087650149579
lambda= 0.164515384563759
lambda= 0.192120839677229
lambda= 0.22435845216639
lambda= 0.26200549166382
lambda= 0.305969652576716
lambda= 0.357310939184576
lambda= 0.417267223026156
lambda= 0.487284088780777
lambda= 0.569049688247448
lambda= 0.664535442773709
lambda= 0.776043575496029
lambda= 0.906262619424709
lambda= 1.05833223970905
lambda= 1.23591893298942
lambda= 1.44330442899635
lambda= 1.6854889258164
lambda= 1.96831164789345
lambda= 2.29859163349676
lambda= 2.68429214613239
lambda= 3.1347126739632
lambda= 3.6607131464672
lambda= 4.27497577434272
lambda= 4.99231082578924
lambda= 5.83001371162726
lambda= 6.80828198880995
lambda= 7.9507023365501
lambda= 9.28481924637094
lambda= 10.8427991375648
lambda= 12.662205910312
lambda= 14.7869066355452
lambda= 17.2681292183268
lambda= 20.165697535686
lambda= 23.5494738288839
lambda= 27.5010431271164
lambda= 32.1156803151964
lambda= 37.5046472724847
lambda= 43.7978754685737
lambda= 51.1470986948335
lambda= 59.7295114640004
lambda= 69.752041284182
lambda= 81.4563378145596
lambda= 95.124599194552
lambda= 111.086376022994
----------- FAILURE REPORT --------------
--- failure: the condition has length > 1 ---
--- srcref ---
:
--- package (from environment) ---
orderedLasso
--- call from context ---
predict.orderedLasso(object = object, newdata = newdata, ...)
--- call from argument ---
if (class(object$beta) == "numeric") {
if (is.null(object$b0)) {
b0 = 0
if (ordered)
b0.ordered = 0
}
else {
b0 = object$b0
if (ordered)
b0.ordered = object$b0.ordered
}
yhat = as.vector(newdata %*% object$beta + b0)
if (ordered)
yhat.ordered = as.vector(newdata %*% object$beta.ordered +
b0.ordered)
} else {
if (is.null(object$b0)) {
b0 = rep(0, length = ncol(object$beta))
if (ordered)
b0.ordered = rep(0, length = ncol(object$beta))
}
else {
b0 = object$b0
if (ordered)
b0.ordered = object$b0.ordered
}
nlam = ncol(object$beta)
yhat = matrix(NA, n, nlam)
if (ordered)
yhat.ordered = matrix(NA, n, nlam)
for (i in seq(nlam)) {
yhat[, i] = as.vector(newdata %*% object$beta[, i] +
b0[i])
if (ordered)
yhat.ordered[, i] = as.vector(newdata %*% object$beta.ordered[,
i] + b0.ordered[i])
}
}
--- R stacktrace ---
where 1: predict.orderedLasso(object = object, newdata = newdata, ...)
where 2: predict.orderedLasso.path(a, newdata = x[folds[[ii]], ])
where 3: orderedLasso.cv(x, y, intercept = FALSE, trace = TRUE, method = "Solve.QP",
strongly.ordered = TRUE)
--- value of length: 2 type: logical ---
[1] FALSE FALSE
--- function from context ---
function (object, newdata, ...)
{
n <- nrow(newdata)
ordered = object$strongly.ordered
if (class(object$beta) == "numeric") {
if (is.null(object$b0)) {
b0 = 0
if (ordered)
b0.ordered = 0
}
else {
b0 = object$b0
if (ordered)
b0.ordered = object$b0.ordered
}
yhat = as.vector(newdata %*% object$beta + b0)
if (ordered)
yhat.ordered = as.vector(newdata %*% object$beta.ordered +
b0.ordered)
}
else {
if (is.null(object$b0)) {
b0 = rep(0, length = ncol(object$beta))
if (ordered)
b0.ordered = rep(0, length = ncol(object$beta))
}
else {
b0 = object$b0
if (ordered)
b0.ordered = object$b0.ordered
}
nlam = ncol(object$beta)
yhat = matrix(NA, n, nlam)
if (ordered)
yhat.ordered = matrix(NA, n, nlam)
for (i in seq(nlam)) {
yhat[, i] = as.vector(newdata %*% object$beta[, i] +
b0[i])
if (ordered)
yhat.ordered[, i] = as.vector(newdata %*% object$beta.ordered[,
i] + b0.ordered[i])
}
}
if (!ordered)
yhat.ordered = NULL
return(list(yhat = yhat, yhat.ordered = yhat.ordered))
}
<bytecode: 0x6d19d78>
<environment: namespace:orderedLasso>
--- function search by body ---
Function predict.orderedLasso in namespace orderedLasso has this body.
----------- END OF FAILURE REPORT --------------
Error in if (class(object$beta) == "numeric") { :
the condition has length > 1
Calls: orderedLasso.cv -> predict.orderedLasso.path -> predict.orderedLasso
Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc