Last updated on 2020-02-19 10:49:02 CET.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 1.0 | 2.22 | 20.81 | 23.03 | ERROR | |
| r-devel-linux-x86_64-debian-gcc | 1.0 | 1.50 | 16.77 | 18.27 | ERROR | |
| r-devel-linux-x86_64-fedora-clang | 1.0 | 28.92 | ERROR | |||
| r-devel-linux-x86_64-fedora-gcc | 1.0 | 27.69 | ERROR | |||
| r-devel-windows-ix86+x86_64 | 1.0 | 5.00 | 35.00 | 40.00 | NOTE | |
| r-devel-windows-ix86+x86_64-gcc8 | 1.0 | 8.00 | 51.00 | 59.00 | NOTE | |
| r-patched-linux-x86_64 | 1.0 | 1.63 | 22.16 | 23.79 | NOTE | |
| r-patched-solaris-x86 | 1.0 | 43.90 | NOTE | |||
| r-release-linux-x86_64 | 1.0 | 1.48 | 22.11 | 23.59 | NOTE | |
| r-release-windows-ix86+x86_64 | 1.0 | 4.00 | 38.00 | 42.00 | NOTE | |
| r-release-osx-x86_64 | 1.0 | NOTE | ||||
| r-oldrel-windows-ix86+x86_64 | 1.0 | 2.00 | 42.00 | 44.00 | NOTE | |
| r-oldrel-osx-x86_64 | 1.0 | NOTE |
Version: 1.0
Check: R code for possible problems
Result: NOTE
consensusMCcov: no visible global function definition for 'var'
consensusMCcov: no visible global function definition for 'cov'
consensusMCindep: no visible global function definition for 'var'
semiparamDPE: no visible binding for global variable 'var'
semiparamDPE: no visible global function definition for 'cov'
semiparamDPE: no visible global function definition for 'runif'
Undefined global functions or variables:
cov runif var
Consider adding
importFrom("stats", "cov", "runif", "var")
to your NAMESPACE file.
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-windows-ix86+x86_64, r-devel-windows-ix86+x86_64-gcc8, r-patched-linux-x86_64, r-patched-solaris-x86, r-release-linux-x86_64, r-release-windows-ix86+x86_64, r-release-osx-x86_64, r-oldrel-windows-ix86+x86_64, r-oldrel-osx-x86_64
Version: 1.0
Check: examples
Result: ERROR
Running examples in 'parallelMCMCcombine-Ex.R' failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: consensusMCcov
> ### Title: Consensus Monte Carlo Algorithm (for correlated parameters)
> ### Aliases: consensusMCcov
> ### Keywords: combine consensus subposterior posterior parallel
>
> ### ** Examples
> d <- 2 # dimension of the parameter space
> sampT <- 1000 # number of subset posterior samples
> M <- 3 # total number of subsets
>
> ## simulate Gaussian subposterior samples
>
> theta <- array(NA,c(d,sampT,M))
>
> norm.mean <- c(1.0, 2.0)
> norm.sd <- c(0.5, 1.0)
>
> for (i in 1:d)
+ for (s in 1:M)
+ theta[i,,s] <- rnorm(sampT, mean=norm.mean[i]+runif(1,-0.01,0.01), sd=norm.sd[i])
>
> ## combine samples:
>
> full.theta <- consensusMCcov(subchain=theta, shuff=FALSE)
----------- FAILURE REPORT --------------
--- failure: the condition has length > 1 ---
--- srcref ---
:
--- package (from environment) ---
parallelMCMCcombine
--- call from context ---
consensusMCcov(subchain = theta, shuff = FALSE)
--- call from argument ---
if (class(res) == "try-error") {
stop(paste("Computation of the inverse of a covariance matrix for",
"one of the sample vectors in the data subset #", k,
"is failed.", "Here is the system R error-message:\n",
attr(res, "condition")))
}
--- R stacktrace ---
where 1: consensusMCcov(subchain = theta, shuff = FALSE)
--- value of length: 2 type: logical ---
[1] FALSE FALSE
--- function from context ---
function (subchain, shuff = FALSE)
{
ddata = length(dim(subchain))
if (ddata != 3) {
stop("The subchain must be an array of dimension c(d,sampletotT,M).")
}
d <- dim(subchain)[1]
sampletotT <- dim(subchain)[2]
M <- dim(subchain)[3]
if (M == 1) {
theta <- array(subchain[, , 1], c(d, sampletotT))
return(theta)
}
if (shuff == TRUE) {
for (k in 1:M) subchain[, , k] <- subchain[, sample(sampletotT),
k]
}
sigmahatm <- array(NA, c(d, d, M))
sigmahatM <- matrix(NA, d, d)
sigmahatM.pre <- matrix(NA, d, d)
if (d == 1) {
for (k in 1:M) {
sigmahatm[1, , k] <- var(subchain[1, , k])
}
}
else {
for (k in 1:M) {
sigmahatm[, , k] <- cov(t(subchain[, , k]))
}
}
sigmahatm.inverse <- array(NA, dim = c(d, d, M))
for (k in 1:M) {
res <- try(sigmahatm.inverse[, , k] <- solve(sigmahatm[,
, k]), silent = TRUE)
if (class(res) == "try-error") {
stop(paste("Computation of the inverse of a covariance matrix for",
"one of the sample vectors in the data subset #",
k, "is failed.", "Here is the system R error-message:\n",
attr(res, "condition")))
}
}
sigmahatM <- solve(rowSums(sigmahatm.inverse, dims = 2))
theta <- matrix(NA, nrow = d, ncol = sampletotT)
wvec <- array(NA, c(d, 1))
for (i in 1:sampletotT) {
wvec <- rep(0, d)
for (s in 1:M) {
wvec <- wvec + sigmahatm.inverse[, , s] %*% subchain[,
i, s]
}
theta[, i] <- sigmahatM %*% wvec
}
return(theta)
}
<bytecode: 0x36d3e20>
<environment: namespace:parallelMCMCcombine>
--- function search by body ---
Function consensusMCcov in namespace parallelMCMCcombine has this body.
----------- END OF FAILURE REPORT --------------
Error in if (class(res) == "try-error") { : the condition has length > 1
Calls: consensusMCcov
Execution halted
Flavor: r-devel-linux-x86_64-debian-clang
Version: 1.0
Check: examples
Result: ERROR
Running examples in ‘parallelMCMCcombine-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: consensusMCcov
> ### Title: Consensus Monte Carlo Algorithm (for correlated parameters)
> ### Aliases: consensusMCcov
> ### Keywords: combine consensus subposterior posterior parallel
>
> ### ** Examples
> d <- 2 # dimension of the parameter space
> sampT <- 1000 # number of subset posterior samples
> M <- 3 # total number of subsets
>
> ## simulate Gaussian subposterior samples
>
> theta <- array(NA,c(d,sampT,M))
>
> norm.mean <- c(1.0, 2.0)
> norm.sd <- c(0.5, 1.0)
>
> for (i in 1:d)
+ for (s in 1:M)
+ theta[i,,s] <- rnorm(sampT, mean=norm.mean[i]+runif(1,-0.01,0.01), sd=norm.sd[i])
>
> ## combine samples:
>
> full.theta <- consensusMCcov(subchain=theta, shuff=FALSE)
----------- FAILURE REPORT --------------
--- failure: the condition has length > 1 ---
--- srcref ---
:
--- package (from environment) ---
parallelMCMCcombine
--- call from context ---
consensusMCcov(subchain = theta, shuff = FALSE)
--- call from argument ---
if (class(res) == "try-error") {
stop(paste("Computation of the inverse of a covariance matrix for",
"one of the sample vectors in the data subset #", k,
"is failed.", "Here is the system R error-message:\n",
attr(res, "condition")))
}
--- R stacktrace ---
where 1: consensusMCcov(subchain = theta, shuff = FALSE)
--- value of length: 2 type: logical ---
[1] FALSE FALSE
--- function from context ---
function (subchain, shuff = FALSE)
{
ddata = length(dim(subchain))
if (ddata != 3) {
stop("The subchain must be an array of dimension c(d,sampletotT,M).")
}
d <- dim(subchain)[1]
sampletotT <- dim(subchain)[2]
M <- dim(subchain)[3]
if (M == 1) {
theta <- array(subchain[, , 1], c(d, sampletotT))
return(theta)
}
if (shuff == TRUE) {
for (k in 1:M) subchain[, , k] <- subchain[, sample(sampletotT),
k]
}
sigmahatm <- array(NA, c(d, d, M))
sigmahatM <- matrix(NA, d, d)
sigmahatM.pre <- matrix(NA, d, d)
if (d == 1) {
for (k in 1:M) {
sigmahatm[1, , k] <- var(subchain[1, , k])
}
}
else {
for (k in 1:M) {
sigmahatm[, , k] <- cov(t(subchain[, , k]))
}
}
sigmahatm.inverse <- array(NA, dim = c(d, d, M))
for (k in 1:M) {
res <- try(sigmahatm.inverse[, , k] <- solve(sigmahatm[,
, k]), silent = TRUE)
if (class(res) == "try-error") {
stop(paste("Computation of the inverse of a covariance matrix for",
"one of the sample vectors in the data subset #",
k, "is failed.", "Here is the system R error-message:\n",
attr(res, "condition")))
}
}
sigmahatM <- solve(rowSums(sigmahatm.inverse, dims = 2))
theta <- matrix(NA, nrow = d, ncol = sampletotT)
wvec <- array(NA, c(d, 1))
for (i in 1:sampletotT) {
wvec <- rep(0, d)
for (s in 1:M) {
wvec <- wvec + sigmahatm.inverse[, , s] %*% subchain[,
i, s]
}
theta[, i] <- sigmahatM %*% wvec
}
return(theta)
}
<bytecode: 0x56509ca39218>
<environment: namespace:parallelMCMCcombine>
--- function search by body ---
Function consensusMCcov in namespace parallelMCMCcombine has this body.
----------- END OF FAILURE REPORT --------------
Error in if (class(res) == "try-error") { : the condition has length > 1
Calls: consensusMCcov
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 1.0
Check: examples
Result: ERROR
Running examples in ‘parallelMCMCcombine-Ex.R’ failed
The error most likely occurred in:
> ### Name: consensusMCcov
> ### Title: Consensus Monte Carlo Algorithm (for correlated parameters)
> ### Aliases: consensusMCcov
> ### Keywords: combine consensus subposterior posterior parallel
>
> ### ** Examples
> d <- 2 # dimension of the parameter space
> sampT <- 1000 # number of subset posterior samples
> M <- 3 # total number of subsets
>
> ## simulate Gaussian subposterior samples
>
> theta <- array(NA,c(d,sampT,M))
>
> norm.mean <- c(1.0, 2.0)
> norm.sd <- c(0.5, 1.0)
>
> for (i in 1:d)
+ for (s in 1:M)
+ theta[i,,s] <- rnorm(sampT, mean=norm.mean[i]+runif(1,-0.01,0.01), sd=norm.sd[i])
>
> ## combine samples:
>
> full.theta <- consensusMCcov(subchain=theta, shuff=FALSE)
----------- FAILURE REPORT --------------
--- failure: the condition has length > 1 ---
--- srcref ---
:
--- package (from environment) ---
parallelMCMCcombine
--- call from context ---
consensusMCcov(subchain = theta, shuff = FALSE)
--- call from argument ---
if (class(res) == "try-error") {
stop(paste("Computation of the inverse of a covariance matrix for",
"one of the sample vectors in the data subset #", k,
"is failed.", "Here is the system R error-message:\n",
attr(res, "condition")))
}
--- R stacktrace ---
where 1: consensusMCcov(subchain = theta, shuff = FALSE)
--- value of length: 2 type: logical ---
[1] FALSE FALSE
--- function from context ---
function (subchain, shuff = FALSE)
{
ddata = length(dim(subchain))
if (ddata != 3) {
stop("The subchain must be an array of dimension c(d,sampletotT,M).")
}
d <- dim(subchain)[1]
sampletotT <- dim(subchain)[2]
M <- dim(subchain)[3]
if (M == 1) {
theta <- array(subchain[, , 1], c(d, sampletotT))
return(theta)
}
if (shuff == TRUE) {
for (k in 1:M) subchain[, , k] <- subchain[, sample(sampletotT),
k]
}
sigmahatm <- array(NA, c(d, d, M))
sigmahatM <- matrix(NA, d, d)
sigmahatM.pre <- matrix(NA, d, d)
if (d == 1) {
for (k in 1:M) {
sigmahatm[1, , k] <- var(subchain[1, , k])
}
}
else {
for (k in 1:M) {
sigmahatm[, , k] <- cov(t(subchain[, , k]))
}
}
sigmahatm.inverse <- array(NA, dim = c(d, d, M))
for (k in 1:M) {
res <- try(sigmahatm.inverse[, , k] <- solve(sigmahatm[,
, k]), silent = TRUE)
if (class(res) == "try-error") {
stop(paste("Computation of the inverse of a covariance matrix for",
"one of the sample vectors in the data subset #",
k, "is failed.", "Here is the system R error-message:\n",
attr(res, "condition")))
}
}
sigmahatM <- solve(rowSums(sigmahatm.inverse, dims = 2))
theta <- matrix(NA, nrow = d, ncol = sampletotT)
wvec <- array(NA, c(d, 1))
for (i in 1:sampletotT) {
wvec <- rep(0, d)
for (s in 1:M) {
wvec <- wvec + sigmahatm.inverse[, , s] %*% subchain[,
i, s]
}
theta[, i] <- sigmahatM %*% wvec
}
return(theta)
}
<bytecode: 0x29bae98>
<environment: namespace:parallelMCMCcombine>
--- function search by body ---
Function consensusMCcov in namespace parallelMCMCcombine has this body.
----------- END OF FAILURE REPORT --------------
Error in if (class(res) == "try-error") { : the condition has length > 1
Calls: consensusMCcov
Execution halted
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 1.0
Check: examples
Result: ERROR
Running examples in ‘parallelMCMCcombine-Ex.R’ failed
The error most likely occurred in:
> ### Name: consensusMCcov
> ### Title: Consensus Monte Carlo Algorithm (for correlated parameters)
> ### Aliases: consensusMCcov
> ### Keywords: combine consensus subposterior posterior parallel
>
> ### ** Examples
> d <- 2 # dimension of the parameter space
> sampT <- 1000 # number of subset posterior samples
> M <- 3 # total number of subsets
>
> ## simulate Gaussian subposterior samples
>
> theta <- array(NA,c(d,sampT,M))
>
> norm.mean <- c(1.0, 2.0)
> norm.sd <- c(0.5, 1.0)
>
> for (i in 1:d)
+ for (s in 1:M)
+ theta[i,,s] <- rnorm(sampT, mean=norm.mean[i]+runif(1,-0.01,0.01), sd=norm.sd[i])
>
> ## combine samples:
>
> full.theta <- consensusMCcov(subchain=theta, shuff=FALSE)
----------- FAILURE REPORT --------------
--- failure: the condition has length > 1 ---
--- srcref ---
:
--- package (from environment) ---
parallelMCMCcombine
--- call from context ---
consensusMCcov(subchain = theta, shuff = FALSE)
--- call from argument ---
if (class(res) == "try-error") {
stop(paste("Computation of the inverse of a covariance matrix for",
"one of the sample vectors in the data subset #", k,
"is failed.", "Here is the system R error-message:\n",
attr(res, "condition")))
}
--- R stacktrace ---
where 1: consensusMCcov(subchain = theta, shuff = FALSE)
--- value of length: 2 type: logical ---
[1] FALSE FALSE
--- function from context ---
function (subchain, shuff = FALSE)
{
ddata = length(dim(subchain))
if (ddata != 3) {
stop("The subchain must be an array of dimension c(d,sampletotT,M).")
}
d <- dim(subchain)[1]
sampletotT <- dim(subchain)[2]
M <- dim(subchain)[3]
if (M == 1) {
theta <- array(subchain[, , 1], c(d, sampletotT))
return(theta)
}
if (shuff == TRUE) {
for (k in 1:M) subchain[, , k] <- subchain[, sample(sampletotT),
k]
}
sigmahatm <- array(NA, c(d, d, M))
sigmahatM <- matrix(NA, d, d)
sigmahatM.pre <- matrix(NA, d, d)
if (d == 1) {
for (k in 1:M) {
sigmahatm[1, , k] <- var(subchain[1, , k])
}
}
else {
for (k in 1:M) {
sigmahatm[, , k] <- cov(t(subchain[, , k]))
}
}
sigmahatm.inverse <- array(NA, dim = c(d, d, M))
for (k in 1:M) {
res <- try(sigmahatm.inverse[, , k] <- solve(sigmahatm[,
, k]), silent = TRUE)
if (class(res) == "try-error") {
stop(paste("Computation of the inverse of a covariance matrix for",
"one of the sample vectors in the data subset #",
k, "is failed.", "Here is the system R error-message:\n",
attr(res, "condition")))
}
}
sigmahatM <- solve(rowSums(sigmahatm.inverse, dims = 2))
theta <- matrix(NA, nrow = d, ncol = sampletotT)
wvec <- array(NA, c(d, 1))
for (i in 1:sampletotT) {
wvec <- rep(0, d)
for (s in 1:M) {
wvec <- wvec + sigmahatm.inverse[, , s] %*% subchain[,
i, s]
}
theta[, i] <- sigmahatM %*% wvec
}
return(theta)
}
<bytecode: 0x39bc860>
<environment: namespace:parallelMCMCcombine>
--- function search by body ---
Function consensusMCcov in namespace parallelMCMCcombine has this body.
----------- END OF FAILURE REPORT --------------
Error in if (class(res) == "try-error") { : the condition has length > 1
Calls: consensusMCcov
Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc