Last updated on 2020-02-19 10:48:50 CET.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 0.1.0 | 2.03 | 21.87 | 23.90 | ERROR | |
| r-devel-linux-x86_64-debian-gcc | 0.1.0 | 1.77 | 17.47 | 19.24 | ERROR | |
| r-devel-linux-x86_64-fedora-clang | 0.1.0 | 29.86 | ERROR | |||
| r-devel-linux-x86_64-fedora-gcc | 0.1.0 | 29.22 | ERROR | |||
| r-devel-windows-ix86+x86_64 | 0.1.0 | 6.00 | 37.00 | 43.00 | OK | |
| r-devel-windows-ix86+x86_64-gcc8 | 0.1.0 | 7.00 | 51.00 | 58.00 | OK | |
| r-patched-linux-x86_64 | 0.1.0 | 1.59 | 22.41 | 24.00 | OK | |
| r-patched-solaris-x86 | 0.1.0 | 43.30 | OK | |||
| r-release-linux-x86_64 | 0.1.0 | 1.69 | 22.65 | 24.34 | OK | |
| r-release-windows-ix86+x86_64 | 0.1.0 | 5.00 | 50.00 | 55.00 | OK | |
| r-release-osx-x86_64 | 0.1.0 | OK | ||||
| r-oldrel-windows-ix86+x86_64 | 0.1.0 | 2.00 | 33.00 | 35.00 | OK | |
| r-oldrel-osx-x86_64 | 0.1.0 | OK |
Version: 0.1.0
Check: examples
Result: ERROR
Running examples in 'designGLMM-Ex.R' failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: findOptimalBlockDesign
> ### Title: Find an efficient block design for a Poisson GLMM
> ### Aliases: findOptimalBlockDesign
>
> ### ** Examples
>
>
> ## Constructing a D-optimal block design with 4 blocks of size 3 with seven treatments
> ## with means c(5,5.5,6,5.5,7,10,4) with between block standard deviation 0.3
> ## and no overdispersion (sigma=0). In each round of simulated annealing, we use 1000
> ## iterations
>
> findOptimalBlockDesign(numblock = 4, blksize = 3, means = c(5,5.5,6,5.5,7,10,4),
+ sigma = 0, sigmaB = 0.3,iter=1000)
The optimal design is:
[,1] [,2] [,3]
[1,] 1 2 3
[2,] 1 6 7
[3,] 2 5 7
[4,] 4 5 6
The determinant of the information matrix is: 0.0789
Progressvec is: 0.0788975256241403
Progressvec is: 0.0788975256241403
$design
[,1] [,2] [,3]
[1,] 1 2 3
[2,] 1 6 7
[3,] 2 5 7
[4,] 4 5 6
$value
[1] 0.07889753
$iter
[1] 0.07889753 0.07889753
>
> ## Constructing an A-optimal design with the same means
>
> findOptimalBlockDesign(numblock = 4, blksize = 3, means = c(5,5.5,6,5.5,7,10,4),
+ sigma = 0, sigmaB = 0.3, criterion = "A",iter=1000)
----------- FAILURE REPORT --------------
--- failure: the condition has length > 1 ---
--- srcref ---
:
--- package (from environment) ---
designGLMM
--- call from context ---
fn(par, ...)
--- call from argument ---
if (class(inversematrix) == "try-error") ret <- 1e+160 else ret <- sum(diag(inversematrix)) -
inversematrix[1, 1]
--- R stacktrace ---
where 1: fn(par, ...)
where 2: (function (par)
fn(par, ...))(c(4, 1, 1, 6, 3, 2, 2, 5, 7, 3, 6, 7))
where 3: stats::optim(workingdes, objfnA_BD, updateDesign_BD, length(means),
blksize, sigmaB, sigma, means, probs, method = "SANN", control = list(maxit = iter,
temp = temp, trace = trace, REPORT = 1, tmax = tmax))
where 4: findOptimalBlockDesign(numblock = 4, blksize = 3, means = c(5,
5.5, 6, 5.5, 7, 10, 4), sigma = 0, sigmaB = 0.3, criterion = "A",
iter = 1000)
--- value of length: 2 type: logical ---
[1] FALSE FALSE
--- function from context ---
function (des, ntmt, blksz, sigb, sige, means, probs = c(1))
{
nblk <- length(des)/blksz
xmeans <- means[des]
diagall <- sigb^2/(sige^2 + 1/xmeans)
ellvec <- matrix(diagall, nrow = blksz)
blk <- apply(ellvec, 2, function(x) diag(x)/sigb^2 - x %*%
t(x) * 1/(sigb^2 * (1 + sqrt(t(x)) %*% sqrt(x)))[1, 1])
oP <- matrix(0, length(des), length(des))
for (q in 1:nblk) {
oP[((q - 1) * blksz + 1):((q - 1) * blksz + blksz), ((q -
1) * blksz + 1):((q - 1) * blksz + blksz)] <- matrix(blk[,
q], nrow = blksz)
}
Xmaster <- cbind(rep(1, ntmt), diag(1, ntmt))
X <- t(sapply(des, function(x) Xmaster[x, ]))
cm <- matrix(0, nrow = ntmt, ncol = ntmt)
cm[upper.tri(cm, diag = FALSE)] <- -1
cm <- cm + diag((ntmt - 1):0)
cm <- cbind(rep(0, ntmt), cm)
cm <- matrix(cm[1:(ntmt - 1), ], nrow = (ntmt - 1))
cm <- rbind(c(1, rep(0, ntmt)), cm)
cm <- cm/rowSums(cm^2)
inversematrix <- try(solve(cm %*% t(X) %*% oP %*% X %*% t(cm)),
silent = TRUE)
if (class(inversematrix) == "try-error")
ret <- 1e+160
else ret <- sum(diag(inversematrix)) - inversematrix[1, 1]
ret
}
<bytecode: 0x3709630>
<environment: namespace:designGLMM>
--- function search by body ---
Function objfnA_BD in namespace designGLMM has this body.
----------- END OF FAILURE REPORT --------------
Error in if (class(inversematrix) == "try-error") ret <- 1e+160 else ret <- sum(diag(inversematrix)) - :
the condition has length > 1
Calls: findOptimalBlockDesign -> <Anonymous> -> <Anonymous> -> fn
Execution halted
Flavor: r-devel-linux-x86_64-debian-clang
Version: 0.1.0
Check: examples
Result: ERROR
Running examples in ‘designGLMM-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: findOptimalBlockDesign
> ### Title: Find an efficient block design for a Poisson GLMM
> ### Aliases: findOptimalBlockDesign
>
> ### ** Examples
>
>
> ## Constructing a D-optimal block design with 4 blocks of size 3 with seven treatments
> ## with means c(5,5.5,6,5.5,7,10,4) with between block standard deviation 0.3
> ## and no overdispersion (sigma=0). In each round of simulated annealing, we use 1000
> ## iterations
>
> findOptimalBlockDesign(numblock = 4, blksize = 3, means = c(5,5.5,6,5.5,7,10,4),
+ sigma = 0, sigmaB = 0.3,iter=1000)
The optimal design is:
[,1] [,2] [,3]
[1,] 1 2 3
[2,] 1 6 7
[3,] 2 5 7
[4,] 4 5 6
The determinant of the information matrix is: 0.0789
Progressvec is: 0.0788975256241403
Progressvec is: 0.0788975256241403
$design
[,1] [,2] [,3]
[1,] 1 2 3
[2,] 1 6 7
[3,] 2 5 7
[4,] 4 5 6
$value
[1] 0.07889753
$iter
[1] 0.07889753 0.07889753
>
> ## Constructing an A-optimal design with the same means
>
> findOptimalBlockDesign(numblock = 4, blksize = 3, means = c(5,5.5,6,5.5,7,10,4),
+ sigma = 0, sigmaB = 0.3, criterion = "A",iter=1000)
----------- FAILURE REPORT --------------
--- failure: the condition has length > 1 ---
--- srcref ---
:
--- package (from environment) ---
designGLMM
--- call from context ---
fn(par, ...)
--- call from argument ---
if (class(inversematrix) == "try-error") ret <- 1e+160 else ret <- sum(diag(inversematrix)) -
inversematrix[1, 1]
--- R stacktrace ---
where 1: fn(par, ...)
where 2: (function (par)
fn(par, ...))(c(4, 1, 1, 6, 3, 2, 2, 5, 7, 3, 6, 7))
where 3: stats::optim(workingdes, objfnA_BD, updateDesign_BD, length(means),
blksize, sigmaB, sigma, means, probs, method = "SANN", control = list(maxit = iter,
temp = temp, trace = trace, REPORT = 1, tmax = tmax))
where 4: findOptimalBlockDesign(numblock = 4, blksize = 3, means = c(5,
5.5, 6, 5.5, 7, 10, 4), sigma = 0, sigmaB = 0.3, criterion = "A",
iter = 1000)
--- value of length: 2 type: logical ---
[1] FALSE FALSE
--- function from context ---
function (des, ntmt, blksz, sigb, sige, means, probs = c(1))
{
nblk <- length(des)/blksz
xmeans <- means[des]
diagall <- sigb^2/(sige^2 + 1/xmeans)
ellvec <- matrix(diagall, nrow = blksz)
blk <- apply(ellvec, 2, function(x) diag(x)/sigb^2 - x %*%
t(x) * 1/(sigb^2 * (1 + sqrt(t(x)) %*% sqrt(x)))[1, 1])
oP <- matrix(0, length(des), length(des))
for (q in 1:nblk) {
oP[((q - 1) * blksz + 1):((q - 1) * blksz + blksz), ((q -
1) * blksz + 1):((q - 1) * blksz + blksz)] <- matrix(blk[,
q], nrow = blksz)
}
Xmaster <- cbind(rep(1, ntmt), diag(1, ntmt))
X <- t(sapply(des, function(x) Xmaster[x, ]))
cm <- matrix(0, nrow = ntmt, ncol = ntmt)
cm[upper.tri(cm, diag = FALSE)] <- -1
cm <- cm + diag((ntmt - 1):0)
cm <- cbind(rep(0, ntmt), cm)
cm <- matrix(cm[1:(ntmt - 1), ], nrow = (ntmt - 1))
cm <- rbind(c(1, rep(0, ntmt)), cm)
cm <- cm/rowSums(cm^2)
inversematrix <- try(solve(cm %*% t(X) %*% oP %*% X %*% t(cm)),
silent = TRUE)
if (class(inversematrix) == "try-error")
ret <- 1e+160
else ret <- sum(diag(inversematrix)) - inversematrix[1, 1]
ret
}
<bytecode: 0x55a24e5f67e0>
<environment: namespace:designGLMM>
--- function search by body ---
Function objfnA_BD in namespace designGLMM has this body.
----------- END OF FAILURE REPORT --------------
Error in if (class(inversematrix) == "try-error") ret <- 1e+160 else ret <- sum(diag(inversematrix)) - :
the condition has length > 1
Calls: findOptimalBlockDesign -> <Anonymous> -> <Anonymous> -> fn
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 0.1.0
Check: examples
Result: ERROR
Running examples in ‘designGLMM-Ex.R’ failed
The error most likely occurred in:
> ### Name: findOptimalBlockDesign
> ### Title: Find an efficient block design for a Poisson GLMM
> ### Aliases: findOptimalBlockDesign
>
> ### ** Examples
>
>
> ## Constructing a D-optimal block design with 4 blocks of size 3 with seven treatments
> ## with means c(5,5.5,6,5.5,7,10,4) with between block standard deviation 0.3
> ## and no overdispersion (sigma=0). In each round of simulated annealing, we use 1000
> ## iterations
>
> findOptimalBlockDesign(numblock = 4, blksize = 3, means = c(5,5.5,6,5.5,7,10,4),
+ sigma = 0, sigmaB = 0.3,iter=1000)
The optimal design is:
[,1] [,2] [,3]
[1,] 1 2 3
[2,] 1 6 7
[3,] 2 5 7
[4,] 4 5 6
The determinant of the information matrix is: 0.0789
Progressvec is: 0.0788975256241403
Progressvec is: 0.0788975256241403
$design
[,1] [,2] [,3]
[1,] 1 2 3
[2,] 1 6 7
[3,] 2 5 7
[4,] 4 5 6
$value
[1] 0.07889753
$iter
[1] 0.07889753 0.07889753
>
> ## Constructing an A-optimal design with the same means
>
> findOptimalBlockDesign(numblock = 4, blksize = 3, means = c(5,5.5,6,5.5,7,10,4),
+ sigma = 0, sigmaB = 0.3, criterion = "A",iter=1000)
----------- FAILURE REPORT --------------
--- failure: the condition has length > 1 ---
--- srcref ---
:
--- package (from environment) ---
designGLMM
--- call from context ---
fn(par, ...)
--- call from argument ---
if (class(inversematrix) == "try-error") ret <- 1e+160 else ret <- sum(diag(inversematrix)) -
inversematrix[1, 1]
--- R stacktrace ---
where 1: fn(par, ...)
where 2: (function (par)
fn(par, ...))(c(4, 1, 1, 6, 3, 2, 2, 5, 7, 3, 6, 7))
where 3: stats::optim(workingdes, objfnA_BD, updateDesign_BD, length(means),
blksize, sigmaB, sigma, means, probs, method = "SANN", control = list(maxit = iter,
temp = temp, trace = trace, REPORT = 1, tmax = tmax))
where 4: findOptimalBlockDesign(numblock = 4, blksize = 3, means = c(5,
5.5, 6, 5.5, 7, 10, 4), sigma = 0, sigmaB = 0.3, criterion = "A",
iter = 1000)
--- value of length: 2 type: logical ---
[1] FALSE FALSE
--- function from context ---
function (des, ntmt, blksz, sigb, sige, means, probs = c(1))
{
nblk <- length(des)/blksz
xmeans <- means[des]
diagall <- sigb^2/(sige^2 + 1/xmeans)
ellvec <- matrix(diagall, nrow = blksz)
blk <- apply(ellvec, 2, function(x) diag(x)/sigb^2 - x %*%
t(x) * 1/(sigb^2 * (1 + sqrt(t(x)) %*% sqrt(x)))[1, 1])
oP <- matrix(0, length(des), length(des))
for (q in 1:nblk) {
oP[((q - 1) * blksz + 1):((q - 1) * blksz + blksz), ((q -
1) * blksz + 1):((q - 1) * blksz + blksz)] <- matrix(blk[,
q], nrow = blksz)
}
Xmaster <- cbind(rep(1, ntmt), diag(1, ntmt))
X <- t(sapply(des, function(x) Xmaster[x, ]))
cm <- matrix(0, nrow = ntmt, ncol = ntmt)
cm[upper.tri(cm, diag = FALSE)] <- -1
cm <- cm + diag((ntmt - 1):0)
cm <- cbind(rep(0, ntmt), cm)
cm <- matrix(cm[1:(ntmt - 1), ], nrow = (ntmt - 1))
cm <- rbind(c(1, rep(0, ntmt)), cm)
cm <- cm/rowSums(cm^2)
inversematrix <- try(solve(cm %*% t(X) %*% oP %*% X %*% t(cm)),
silent = TRUE)
if (class(inversematrix) == "try-error")
ret <- 1e+160
else ret <- sum(diag(inversematrix)) - inversematrix[1, 1]
ret
}
<bytecode: 0x1b81628>
<environment: namespace:designGLMM>
--- function search by body ---
Function objfnA_BD in namespace designGLMM has this body.
----------- END OF FAILURE REPORT --------------
Error in if (class(inversematrix) == "try-error") ret <- 1e+160 else ret <- sum(diag(inversematrix)) - :
the condition has length > 1
Calls: findOptimalBlockDesign -> <Anonymous> -> <Anonymous> -> fn
Execution halted
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 0.1.0
Check: examples
Result: ERROR
Running examples in ‘designGLMM-Ex.R’ failed
The error most likely occurred in:
> ### Name: findOptimalBlockDesign
> ### Title: Find an efficient block design for a Poisson GLMM
> ### Aliases: findOptimalBlockDesign
>
> ### ** Examples
>
>
> ## Constructing a D-optimal block design with 4 blocks of size 3 with seven treatments
> ## with means c(5,5.5,6,5.5,7,10,4) with between block standard deviation 0.3
> ## and no overdispersion (sigma=0). In each round of simulated annealing, we use 1000
> ## iterations
>
> findOptimalBlockDesign(numblock = 4, blksize = 3, means = c(5,5.5,6,5.5,7,10,4),
+ sigma = 0, sigmaB = 0.3,iter=1000)
The optimal design is:
[,1] [,2] [,3]
[1,] 1 2 3
[2,] 1 6 7
[3,] 2 5 7
[4,] 4 5 6
The determinant of the information matrix is: 0.0789
Progressvec is: 0.0788975256241403
Progressvec is: 0.0788975256241403
$design
[,1] [,2] [,3]
[1,] 1 2 3
[2,] 1 6 7
[3,] 2 5 7
[4,] 4 5 6
$value
[1] 0.07889753
$iter
[1] 0.07889753 0.07889753
>
> ## Constructing an A-optimal design with the same means
>
> findOptimalBlockDesign(numblock = 4, blksize = 3, means = c(5,5.5,6,5.5,7,10,4),
+ sigma = 0, sigmaB = 0.3, criterion = "A",iter=1000)
----------- FAILURE REPORT --------------
--- failure: the condition has length > 1 ---
--- srcref ---
:
--- package (from environment) ---
designGLMM
--- call from context ---
fn(par, ...)
--- call from argument ---
if (class(inversematrix) == "try-error") ret <- 1e+160 else ret <- sum(diag(inversematrix)) -
inversematrix[1, 1]
--- R stacktrace ---
where 1: fn(par, ...)
where 2: (function (par)
fn(par, ...))(c(4, 1, 1, 6, 3, 2, 2, 5, 7, 3, 6, 7))
where 3: stats::optim(workingdes, objfnA_BD, updateDesign_BD, length(means),
blksize, sigmaB, sigma, means, probs, method = "SANN", control = list(maxit = iter,
temp = temp, trace = trace, REPORT = 1, tmax = tmax))
where 4: findOptimalBlockDesign(numblock = 4, blksize = 3, means = c(5,
5.5, 6, 5.5, 7, 10, 4), sigma = 0, sigmaB = 0.3, criterion = "A",
iter = 1000)
--- value of length: 2 type: logical ---
[1] FALSE FALSE
--- function from context ---
function (des, ntmt, blksz, sigb, sige, means, probs = c(1))
{
nblk <- length(des)/blksz
xmeans <- means[des]
diagall <- sigb^2/(sige^2 + 1/xmeans)
ellvec <- matrix(diagall, nrow = blksz)
blk <- apply(ellvec, 2, function(x) diag(x)/sigb^2 - x %*%
t(x) * 1/(sigb^2 * (1 + sqrt(t(x)) %*% sqrt(x)))[1, 1])
oP <- matrix(0, length(des), length(des))
for (q in 1:nblk) {
oP[((q - 1) * blksz + 1):((q - 1) * blksz + blksz), ((q -
1) * blksz + 1):((q - 1) * blksz + blksz)] <- matrix(blk[,
q], nrow = blksz)
}
Xmaster <- cbind(rep(1, ntmt), diag(1, ntmt))
X <- t(sapply(des, function(x) Xmaster[x, ]))
cm <- matrix(0, nrow = ntmt, ncol = ntmt)
cm[upper.tri(cm, diag = FALSE)] <- -1
cm <- cm + diag((ntmt - 1):0)
cm <- cbind(rep(0, ntmt), cm)
cm <- matrix(cm[1:(ntmt - 1), ], nrow = (ntmt - 1))
cm <- rbind(c(1, rep(0, ntmt)), cm)
cm <- cm/rowSums(cm^2)
inversematrix <- try(solve(cm %*% t(X) %*% oP %*% X %*% t(cm)),
silent = TRUE)
if (class(inversematrix) == "try-error")
ret <- 1e+160
else ret <- sum(diag(inversematrix)) - inversematrix[1, 1]
ret
}
<bytecode: 0x2de2678>
<environment: namespace:designGLMM>
--- function search by body ---
Function objfnA_BD in namespace designGLMM has this body.
----------- END OF FAILURE REPORT --------------
Error in if (class(inversematrix) == "try-error") ret <- 1e+160 else ret <- sum(diag(inversematrix)) - :
the condition has length > 1
Calls: findOptimalBlockDesign -> <Anonymous> -> <Anonymous> -> fn
Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc