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$beta.ordered[, 
                  i] + b0.ordered[i])
        }
    }
    if (!ordered) 
        yhat.ordered = NULL
    return(list(yhat = yhat, yhat.ordered = yhat.ordered))
}
<bytecode: 0x778a178>
<environment: namespace:orderedLasso>
 --- function search by body ---
Function predict.orderedLasso in namespace orderedLasso has this body.
 ----------- END OF FAILURE REPORT -------------- 
Error in if (class(object$beta) == "numeric") { : 
  the condition has length > 1
Calls: orderedLasso.cv -> predict.orderedLasso.path -> predict.orderedLasso
Execution halted