Last updated on 2020-02-19 10:49:00 CET.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 0.2 | 39.19 | 61.05 | 100.24 | ERROR | |
| r-devel-linux-x86_64-debian-gcc | 0.2 | 27.64 | 48.26 | 75.90 | ERROR | |
| r-devel-linux-x86_64-fedora-clang | 0.2 | 128.13 | ERROR | |||
| r-devel-linux-x86_64-fedora-gcc | 0.2 | 124.44 | ERROR | |||
| r-devel-windows-ix86+x86_64 | 0.2 | 57.00 | 98.00 | 155.00 | OK | |
| r-devel-windows-ix86+x86_64-gcc8 | 0.2 | 93.00 | 131.00 | 224.00 | OK | |
| r-patched-linux-x86_64 | 0.2 | 28.97 | 53.60 | 82.57 | OK | |
| r-patched-solaris-x86 | 0.2 | 152.00 | OK | |||
| r-release-linux-x86_64 | 0.2 | 29.28 | 53.64 | 82.92 | OK | |
| r-release-windows-ix86+x86_64 | 0.2 | 66.00 | 96.00 | 162.00 | OK | |
| r-release-osx-x86_64 | 0.2 | OK | ||||
| r-oldrel-windows-ix86+x86_64 | 0.2 | 49.00 | 83.00 | 132.00 | OK | |
| r-oldrel-osx-x86_64 | 0.2 | OK |
Version: 0.2
Check: examples
Result: ERROR
Running examples in 'netcoh-Ex.R' failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: predict.rncReg
> ### Title: make predictions from a "rncReg" object.
> ### Aliases: predict.rncReg
> ### Keywords: models networks regression
>
> ### ** Examples
>
> set.seed(100)
>
> A <- matrix(0,200,200)
> A[1:100,1:100] <- 1
> A[101:200,101:200] <- 1
> diag(A) <- 0
>
> alpha <- c(rep(1,100),rep(-1,100)) + rnorm(200)*0.5
> A <- A[c(1:50,101:150,51:100,151:200),c(1:50,101:150,51:100,151:200)]
> alpha <- alpha[c(1:50,101:150,51:100,151:200)]
>
> beta <- rnorm(2)
>
> X <- matrix(rnorm(400),ncol=2)
>
> Y <- X
>
> A1 <- A[1:100,1:100]
> X1 <- X[1:100,]
> Y1 <- matrix(Y[1:100],ncol=1)
>
>
> ## If one wants to regularize the Laplacian by
> ## using gamma > 0 in rncreg, we suggest use
> ## centered data.
> #mean.x <- colMeans(X1)
> #mean.y <- mean(Y1)
> #Y1 <- Y1-mean.y
> #X1 <- t(t(X1)-mean.x)
> #Y <- Y-mean.y
> #X <- t(t(X)-mean.x)
>
>
>
> m <- rncreg(A=A1,X=X1,Y=Y1,model="linear",lambda=10,gamma=0,cv=5)
----------- FAILURE REPORT --------------
--- failure: the condition has length > 1 ---
--- srcref ---
:
--- package (from environment) ---
netcoh
--- call from context ---
rncreg(A = A1, X = X1, Y = Y1, model = "linear", lambda = 10,
gamma = 0, cv = 5)
--- call from argument ---
if (class(X) != "matrix") stop("X should be a matrix!")
--- R stacktrace ---
where 1: rncreg(A = A1, X = X1, Y = Y1, model = "linear", lambda = 10,
gamma = 0, cv = 5)
--- value of length: 2 type: logical ---
[1] FALSE TRUE
--- function from context ---
function (A, lambda, Y = NULL, X = NULL, dt = NULL, gamma = 0.05,
model = c("linear", "logistic", "cox"), max.iter = 50, tol = 1e-04,
init = NULL, cv = NULL, cv.seed = 999, low.dim = NULL, verbose = FALSE)
{
if (length(model) > 1)
model <- model[1]
if (!any(c("linear", "logistic", "cox") == model))
stop("model must be one of linear, logistic and cox.")
n <- nrow(A)
if (norm(t(A) - A, "F") > 0)
warning("A is not symmetric....")
if (!is.null(X)) {
if (class(X) != "matrix")
stop("X should be a matrix!")
if (nrow(X) != n)
stop("Dimensions do not match!")
}
if (!is.null(Y)) {
if (class(Y) != "matrix")
stop("Y should be a matrix!")
if (nrow(Y) != n)
stop("Dimensions do not match!")
}
if (!is.null(dt)) {
if (nrow(dt) != n)
stop("Dimensions do not match!")
if (class(dt) != "data.frame")
stop("dt must be a data.frame!")
}
if (model == "linear") {
result <- rnc.linear(X = X, Y = Y, A = A, lambda = lambda,
gamma = gamma, cv = cv, cv.seed = cv.seed, low.dim = low.dim)
result.obj <- list(alpha = result$alpha, beta = result$beta,
A = A, lambda = lambda, X = X, Y = Y, dt = dt, gamma = gamma,
cv = cv, cv.loss = result$cv.MSE, cv.sd = result$cv.sd,
model = model)
class(result.obj) <- "rncReg"
return(result.obj)
}
if (model == "logistic") {
result <- rnc.logistic(X = X, Y = Y, A = A, lambda = lambda,
gamma = gamma, cv = cv, cv.seed = cv.seed, max.iter = max.iter,
tol = tol, init = init, verbose = verbose)
result.obj <- list(alpha = result$alpha, beta = result$beta,
A = A, lambda = lambda, X = X, Y = Y, dt = dt, gamma = gamma,
cv = cv, cv.loss = result$cv.dev, cv.sd = result$cv.sd,
model = model)
class(result.obj) <- "rncReg"
return(result.obj)
}
if (model == "cox") {
result <- rnc.cox(X = X, dt = dt, A = A, lambda = lambda,
gamma = gamma, cv = cv, cv.seed = cv.seed, max.iter = max.iter,
tol = tol, init = init, verbose = verbose)
result.obj <- list(alpha = result$alpha, beta = result$beta,
A = A, lambda = lambda, X = X, Y = Y, dt = dt, gamma = gamma,
cv = cv, cv.loss = result$cv.dev, cv.sd = result$cv.sd,
model = model)
class(result.obj) <- "rncReg"
return(result.obj)
}
}
<bytecode: 0xc0800d0>
<environment: namespace:netcoh>
--- function search by body ---
Function rncreg in namespace netcoh has this body.
----------- END OF FAILURE REPORT --------------
Error in if (class(X) != "matrix") stop("X should be a matrix!") :
the condition has length > 1
Calls: rncreg
Execution halted
Flavor: r-devel-linux-x86_64-debian-clang
Version: 0.2
Check: examples
Result: ERROR
Running examples in ‘netcoh-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: predict.rncReg
> ### Title: make predictions from a "rncReg" object.
> ### Aliases: predict.rncReg
> ### Keywords: models networks regression
>
> ### ** Examples
>
> set.seed(100)
>
> A <- matrix(0,200,200)
> A[1:100,1:100] <- 1
> A[101:200,101:200] <- 1
> diag(A) <- 0
>
> alpha <- c(rep(1,100),rep(-1,100)) + rnorm(200)*0.5
> A <- A[c(1:50,101:150,51:100,151:200),c(1:50,101:150,51:100,151:200)]
> alpha <- alpha[c(1:50,101:150,51:100,151:200)]
>
> beta <- rnorm(2)
>
> X <- matrix(rnorm(400),ncol=2)
>
> Y <- X
>
> A1 <- A[1:100,1:100]
> X1 <- X[1:100,]
> Y1 <- matrix(Y[1:100],ncol=1)
>
>
> ## If one wants to regularize the Laplacian by
> ## using gamma > 0 in rncreg, we suggest use
> ## centered data.
> #mean.x <- colMeans(X1)
> #mean.y <- mean(Y1)
> #Y1 <- Y1-mean.y
> #X1 <- t(t(X1)-mean.x)
> #Y <- Y-mean.y
> #X <- t(t(X)-mean.x)
>
>
>
> m <- rncreg(A=A1,X=X1,Y=Y1,model="linear",lambda=10,gamma=0,cv=5)
----------- FAILURE REPORT --------------
--- failure: the condition has length > 1 ---
--- srcref ---
:
--- package (from environment) ---
netcoh
--- call from context ---
rncreg(A = A1, X = X1, Y = Y1, model = "linear", lambda = 10,
gamma = 0, cv = 5)
--- call from argument ---
if (class(X) != "matrix") stop("X should be a matrix!")
--- R stacktrace ---
where 1: rncreg(A = A1, X = X1, Y = Y1, model = "linear", lambda = 10,
gamma = 0, cv = 5)
--- value of length: 2 type: logical ---
[1] FALSE TRUE
--- function from context ---
function (A, lambda, Y = NULL, X = NULL, dt = NULL, gamma = 0.05,
model = c("linear", "logistic", "cox"), max.iter = 50, tol = 1e-04,
init = NULL, cv = NULL, cv.seed = 999, low.dim = NULL, verbose = FALSE)
{
if (length(model) > 1)
model <- model[1]
if (!any(c("linear", "logistic", "cox") == model))
stop("model must be one of linear, logistic and cox.")
n <- nrow(A)
if (norm(t(A) - A, "F") > 0)
warning("A is not symmetric....")
if (!is.null(X)) {
if (class(X) != "matrix")
stop("X should be a matrix!")
if (nrow(X) != n)
stop("Dimensions do not match!")
}
if (!is.null(Y)) {
if (class(Y) != "matrix")
stop("Y should be a matrix!")
if (nrow(Y) != n)
stop("Dimensions do not match!")
}
if (!is.null(dt)) {
if (nrow(dt) != n)
stop("Dimensions do not match!")
if (class(dt) != "data.frame")
stop("dt must be a data.frame!")
}
if (model == "linear") {
result <- rnc.linear(X = X, Y = Y, A = A, lambda = lambda,
gamma = gamma, cv = cv, cv.seed = cv.seed, low.dim = low.dim)
result.obj <- list(alpha = result$alpha, beta = result$beta,
A = A, lambda = lambda, X = X, Y = Y, dt = dt, gamma = gamma,
cv = cv, cv.loss = result$cv.MSE, cv.sd = result$cv.sd,
model = model)
class(result.obj) <- "rncReg"
return(result.obj)
}
if (model == "logistic") {
result <- rnc.logistic(X = X, Y = Y, A = A, lambda = lambda,
gamma = gamma, cv = cv, cv.seed = cv.seed, max.iter = max.iter,
tol = tol, init = init, verbose = verbose)
result.obj <- list(alpha = result$alpha, beta = result$beta,
A = A, lambda = lambda, X = X, Y = Y, dt = dt, gamma = gamma,
cv = cv, cv.loss = result$cv.dev, cv.sd = result$cv.sd,
model = model)
class(result.obj) <- "rncReg"
return(result.obj)
}
if (model == "cox") {
result <- rnc.cox(X = X, dt = dt, A = A, lambda = lambda,
gamma = gamma, cv = cv, cv.seed = cv.seed, max.iter = max.iter,
tol = tol, init = init, verbose = verbose)
result.obj <- list(alpha = result$alpha, beta = result$beta,
A = A, lambda = lambda, X = X, Y = Y, dt = dt, gamma = gamma,
cv = cv, cv.loss = result$cv.dev, cv.sd = result$cv.sd,
model = model)
class(result.obj) <- "rncReg"
return(result.obj)
}
}
<bytecode: 0x55897df4d4a8>
<environment: namespace:netcoh>
--- function search by body ---
Function rncreg in namespace netcoh has this body.
----------- END OF FAILURE REPORT --------------
Error in if (class(X) != "matrix") stop("X should be a matrix!") :
the condition has length > 1
Calls: rncreg
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 0.2
Check: compiled code
Result: NOTE
File ‘netcoh/libs/netcoh.so’:
Found no calls to: ‘R_registerRoutines’, ‘R_useDynamicSymbols’
It is good practice to register native routines and to disable symbol
search.
See ‘Writing portable packages’ in the ‘Writing R Extensions’ manual.
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc
Version: 0.2
Check: examples
Result: ERROR
Running examples in ‘netcoh-Ex.R’ failed
The error most likely occurred in:
> ### Name: predict.rncReg
> ### Title: make predictions from a "rncReg" object.
> ### Aliases: predict.rncReg
> ### Keywords: models networks regression
>
> ### ** Examples
>
> set.seed(100)
>
> A <- matrix(0,200,200)
> A[1:100,1:100] <- 1
> A[101:200,101:200] <- 1
> diag(A) <- 0
>
> alpha <- c(rep(1,100),rep(-1,100)) + rnorm(200)*0.5
> A <- A[c(1:50,101:150,51:100,151:200),c(1:50,101:150,51:100,151:200)]
> alpha <- alpha[c(1:50,101:150,51:100,151:200)]
>
> beta <- rnorm(2)
>
> X <- matrix(rnorm(400),ncol=2)
>
> Y <- X
>
> A1 <- A[1:100,1:100]
> X1 <- X[1:100,]
> Y1 <- matrix(Y[1:100],ncol=1)
>
>
> ## If one wants to regularize the Laplacian by
> ## using gamma > 0 in rncreg, we suggest use
> ## centered data.
> #mean.x <- colMeans(X1)
> #mean.y <- mean(Y1)
> #Y1 <- Y1-mean.y
> #X1 <- t(t(X1)-mean.x)
> #Y <- Y-mean.y
> #X <- t(t(X)-mean.x)
>
>
>
> m <- rncreg(A=A1,X=X1,Y=Y1,model="linear",lambda=10,gamma=0,cv=5)
----------- FAILURE REPORT --------------
--- failure: the condition has length > 1 ---
--- srcref ---
:
--- package (from environment) ---
netcoh
--- call from context ---
rncreg(A = A1, X = X1, Y = Y1, model = "linear", lambda = 10,
gamma = 0, cv = 5)
--- call from argument ---
if (class(X) != "matrix") stop("X should be a matrix!")
--- R stacktrace ---
where 1: rncreg(A = A1, X = X1, Y = Y1, model = "linear", lambda = 10,
gamma = 0, cv = 5)
--- value of length: 2 type: logical ---
[1] FALSE TRUE
--- function from context ---
function (A, lambda, Y = NULL, X = NULL, dt = NULL, gamma = 0.05,
model = c("linear", "logistic", "cox"), max.iter = 50, tol = 1e-04,
init = NULL, cv = NULL, cv.seed = 999, low.dim = NULL, verbose = FALSE)
{
if (length(model) > 1)
model <- model[1]
if (!any(c("linear", "logistic", "cox") == model))
stop("model must be one of linear, logistic and cox.")
n <- nrow(A)
if (norm(t(A) - A, "F") > 0)
warning("A is not symmetric....")
if (!is.null(X)) {
if (class(X) != "matrix")
stop("X should be a matrix!")
if (nrow(X) != n)
stop("Dimensions do not match!")
}
if (!is.null(Y)) {
if (class(Y) != "matrix")
stop("Y should be a matrix!")
if (nrow(Y) != n)
stop("Dimensions do not match!")
}
if (!is.null(dt)) {
if (nrow(dt) != n)
stop("Dimensions do not match!")
if (class(dt) != "data.frame")
stop("dt must be a data.frame!")
}
if (model == "linear") {
result <- rnc.linear(X = X, Y = Y, A = A, lambda = lambda,
gamma = gamma, cv = cv, cv.seed = cv.seed, low.dim = low.dim)
result.obj <- list(alpha = result$alpha, beta = result$beta,
A = A, lambda = lambda, X = X, Y = Y, dt = dt, gamma = gamma,
cv = cv, cv.loss = result$cv.MSE, cv.sd = result$cv.sd,
model = model)
class(result.obj) <- "rncReg"
return(result.obj)
}
if (model == "logistic") {
result <- rnc.logistic(X = X, Y = Y, A = A, lambda = lambda,
gamma = gamma, cv = cv, cv.seed = cv.seed, max.iter = max.iter,
tol = tol, init = init, verbose = verbose)
result.obj <- list(alpha = result$alpha, beta = result$beta,
A = A, lambda = lambda, X = X, Y = Y, dt = dt, gamma = gamma,
cv = cv, cv.loss = result$cv.dev, cv.sd = result$cv.sd,
model = model)
class(result.obj) <- "rncReg"
return(result.obj)
}
if (model == "cox") {
result <- rnc.cox(X = X, dt = dt, A = A, lambda = lambda,
gamma = gamma, cv = cv, cv.seed = cv.seed, max.iter = max.iter,
tol = tol, init = init, verbose = verbose)
result.obj <- list(alpha = result$alpha, beta = result$beta,
A = A, lambda = lambda, X = X, Y = Y, dt = dt, gamma = gamma,
cv = cv, cv.loss = result$cv.dev, cv.sd = result$cv.sd,
model = model)
class(result.obj) <- "rncReg"
return(result.obj)
}
}
<bytecode: 0xc604948>
<environment: namespace:netcoh>
--- function search by body ---
Function rncreg in namespace netcoh has this body.
----------- END OF FAILURE REPORT --------------
Error in if (class(X) != "matrix") stop("X should be a matrix!") :
the condition has length > 1
Calls: rncreg
Execution halted
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 0.2
Check: examples
Result: ERROR
Running examples in ‘netcoh-Ex.R’ failed
The error most likely occurred in:
> ### Name: predict.rncReg
> ### Title: make predictions from a "rncReg" object.
> ### Aliases: predict.rncReg
> ### Keywords: models networks regression
>
> ### ** Examples
>
> set.seed(100)
>
> A <- matrix(0,200,200)
> A[1:100,1:100] <- 1
> A[101:200,101:200] <- 1
> diag(A) <- 0
>
> alpha <- c(rep(1,100),rep(-1,100)) + rnorm(200)*0.5
> A <- A[c(1:50,101:150,51:100,151:200),c(1:50,101:150,51:100,151:200)]
> alpha <- alpha[c(1:50,101:150,51:100,151:200)]
>
> beta <- rnorm(2)
>
> X <- matrix(rnorm(400),ncol=2)
>
> Y <- X
>
> A1 <- A[1:100,1:100]
> X1 <- X[1:100,]
> Y1 <- matrix(Y[1:100],ncol=1)
>
>
> ## If one wants to regularize the Laplacian by
> ## using gamma > 0 in rncreg, we suggest use
> ## centered data.
> #mean.x <- colMeans(X1)
> #mean.y <- mean(Y1)
> #Y1 <- Y1-mean.y
> #X1 <- t(t(X1)-mean.x)
> #Y <- Y-mean.y
> #X <- t(t(X)-mean.x)
>
>
>
> m <- rncreg(A=A1,X=X1,Y=Y1,model="linear",lambda=10,gamma=0,cv=5)
----------- FAILURE REPORT --------------
--- failure: the condition has length > 1 ---
--- srcref ---
:
--- package (from environment) ---
netcoh
--- call from context ---
rncreg(A = A1, X = X1, Y = Y1, model = "linear", lambda = 10,
gamma = 0, cv = 5)
--- call from argument ---
if (class(X) != "matrix") stop("X should be a matrix!")
--- R stacktrace ---
where 1: rncreg(A = A1, X = X1, Y = Y1, model = "linear", lambda = 10,
gamma = 0, cv = 5)
--- value of length: 2 type: logical ---
[1] FALSE TRUE
--- function from context ---
function (A, lambda, Y = NULL, X = NULL, dt = NULL, gamma = 0.05,
model = c("linear", "logistic", "cox"), max.iter = 50, tol = 1e-04,
init = NULL, cv = NULL, cv.seed = 999, low.dim = NULL, verbose = FALSE)
{
if (length(model) > 1)
model <- model[1]
if (!any(c("linear", "logistic", "cox") == model))
stop("model must be one of linear, logistic and cox.")
n <- nrow(A)
if (norm(t(A) - A, "F") > 0)
warning("A is not symmetric....")
if (!is.null(X)) {
if (class(X) != "matrix")
stop("X should be a matrix!")
if (nrow(X) != n)
stop("Dimensions do not match!")
}
if (!is.null(Y)) {
if (class(Y) != "matrix")
stop("Y should be a matrix!")
if (nrow(Y) != n)
stop("Dimensions do not match!")
}
if (!is.null(dt)) {
if (nrow(dt) != n)
stop("Dimensions do not match!")
if (class(dt) != "data.frame")
stop("dt must be a data.frame!")
}
if (model == "linear") {
result <- rnc.linear(X = X, Y = Y, A = A, lambda = lambda,
gamma = gamma, cv = cv, cv.seed = cv.seed, low.dim = low.dim)
result.obj <- list(alpha = result$alpha, beta = result$beta,
A = A, lambda = lambda, X = X, Y = Y, dt = dt, gamma = gamma,
cv = cv, cv.loss = result$cv.MSE, cv.sd = result$cv.sd,
model = model)
class(result.obj) <- "rncReg"
return(result.obj)
}
if (model == "logistic") {
result <- rnc.logistic(X = X, Y = Y, A = A, lambda = lambda,
gamma = gamma, cv = cv, cv.seed = cv.seed, max.iter = max.iter,
tol = tol, init = init, verbose = verbose)
result.obj <- list(alpha = result$alpha, beta = result$beta,
A = A, lambda = lambda, X = X, Y = Y, dt = dt, gamma = gamma,
cv = cv, cv.loss = result$cv.dev, cv.sd = result$cv.sd,
model = model)
class(result.obj) <- "rncReg"
return(result.obj)
}
if (model == "cox") {
result <- rnc.cox(X = X, dt = dt, A = A, lambda = lambda,
gamma = gamma, cv = cv, cv.seed = cv.seed, max.iter = max.iter,
tol = tol, init = init, verbose = verbose)
result.obj <- list(alpha = result$alpha, beta = result$beta,
A = A, lambda = lambda, X = X, Y = Y, dt = dt, gamma = gamma,
cv = cv, cv.loss = result$cv.dev, cv.sd = result$cv.sd,
model = model)
class(result.obj) <- "rncReg"
return(result.obj)
}
}
<bytecode: 0xd7a8900>
<environment: namespace:netcoh>
--- function search by body ---
Function rncreg in namespace netcoh has this body.
----------- END OF FAILURE REPORT --------------
Error in if (class(X) != "matrix") stop("X should be a matrix!") :
the condition has length > 1
Calls: rncreg
Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc