CRAN Package Check Results for Package GUIgems

Last updated on 2020-02-19 10:48:55 CET.

Check Details

Version: 0.1
Check: examples
Result: ERROR
    Running examples in 'GUIgems-Ex.R' failed
    The error most likely occurred in:
    
    > base::assign(".ptime", proc.time(), pos = "CheckExEnv")
    > ### Name: mergeStates
    > ### Title: mergeStates
    > ### Aliases: mergeStates
    > ### Keywords: merge mergeStates,
    >
    > ### ** Examples
    >
    >
    > hfNames <- array(rep("Exponential", 16), dim = c(4,4))
    > hfNames[col(hfNames) <= row(hfNames)]<-"NULL"
    > rownames(hfNames) <- as.list(paste("state", 1:4))
    > colnames(hfNames) <- as.list(paste("state", 1:4))
    > M <- makeM(hfNames)
    [1] "state 1" "state 2" "state 3" "state 4"
     to
    from state 1 state 2 state 3 state 4
     state 1 NULL "impossible" "impossible" "impossible"
     state 2 NULL NULL "impossible" "impossible"
     state 3 NULL NULL NULL "impossible"
     state 4 NULL NULL NULL NULL
    > param <- generateParameterMatrix(M)
    > param[[1,2]] <- list(rate = 1)
    > param[[1,3]] <- list(rate = 2)
    > param[[2,3]] <- list(rate = 0.5)
    >
    > param[[1,4]] <- list(rate = 1)
    > param[[2,4]] <- list(rate = 2)
    > param[[3,4]] <- list(rate = 0.5)
    >
    > cohort <- simulateCohort(
    + transitionFunctions = M,
    + parameters = param,
    + cohortSize = 100,
    + to=10)
    [1] "class(parameters)"
    [1] "transition.structure"
    attr(,"package")
    [1] "GUIgems"
     to
    from state 1 state 2 state 3 state 4
     state 1 NULL List,1 List,1 List,1
     state 2 NULL NULL List,1 List,1
     state 3 NULL NULL NULL List,1
     state 4 NULL NULL NULL NULL
     ----------- FAILURE REPORT --------------
     --- failure: the condition has length > 1 ---
     --- srcref ---
    :
     --- package (from environment) ---
    GUIgems
     --- call from context ---
    createCohorts(hazardf = hf, statesNumber = statesNumber, cohortSize = cohortSize,
     mu = parameters.in, sigma = sigma, historyl = historyDep,
     impossible = impossible, fixpar = fixpar, direct = direct,
     bl0 = baseline, startingStates = initialState, absorbing = absorbing,
     to = to, report.every = report.every, sampler.steps = sampler.steps)
     --- call from argument ---
    if (class(sigma) == "transition.structure") {
     if (dim(sigma)[1] != length(unlist(mu)))
     stop("size of parameters and parameterCovariances are inconsistent")
    }
     --- R stacktrace ---
    where 1: createCohorts(hazardf = hf, statesNumber = statesNumber, cohortSize = cohortSize,
     mu = parameters.in, sigma = sigma, historyl = historyDep,
     impossible = impossible, fixpar = fixpar, direct = direct,
     bl0 = baseline, startingStates = initialState, absorbing = absorbing,
     to = to, report.every = report.every, sampler.steps = sampler.steps)
    where 2: simulateCohort(transitionFunctions = M, parameters = param, cohortSize = 100,
     to = 10)
    
     --- value of length: 2 type: logical ---
    [1] FALSE FALSE
     --- function from context ---
    function (hazardf, statesNumber, statesNamesFrom = strsplit((dimnames(hazardf)["from"])[[1]],
     " "), statesNamesTo = statesNamesFrom, cohortSize, mu, sigma = matrix(0,
     nrow = length(unlist(mu)), ncol = length(unlist(mu))), historyl = FALSE,
     startingStates = rep(1, cohortSize), absorbing = cohortSize,
     impossible = NULL, fixpar = NULL, direct = NULL, bl0 = matrix(0,
     nrow = cohortSize), to = 100, report.every, sampler.steps)
    {
     statesNames <- list(from = statesNamesFrom, to = statesNamesTo)
     hazardf <- t(hazardf)[t(auxcounter(statesNumber)) > 0]
     if (length(hazardf) < (statesNumber * (statesNumber - 1)/2)) {
     length(hazardf) <- statesNumber * (statesNumber - 1)/2
     }
     for (tr in 1:length(hazardf)) {
     if (length(hazardf[[tr]]) > 0) {
     if (!is.function(hazardf[[tr]])) {
     if (!hazardf[[tr]] %in% c("Weibull", "multWeibull",
     "Exponential", "impossible") && !is.na(hazardf[[tr]]))
     try(hazardf[[tr]] <- as.function(hazardf[[tr]]))
     }
     }
     }
     mu <- as.list(unlist(t(mu), recursive = FALSE))
     if (length(mu) > 0) {
     mu <- lapply(mu, as.numeric)
     }
     if (class(sigma) == "transition.structure") {
     if (dim(sigma)[1] != length(unlist(mu)))
     stop("size of parameters and parameterCovariances are inconsistent")
     }
     if (length(startingStates) == 1)
     rep(startingStates, cohortSize)
     if (cohortSize > 1) {
     try(bl0 <- as.matrix(bl0))
     }
     else if (is.null(dim(bl0))) {
     try(bl0 <- t(as.matrix(bl0)))
     }
     if (nrow(bl0) != cohortSize)
     warning("baseline is not of the right dimension")
     for (i in 1:length(hazardf)) {
     if (is.element(i, impossible)) {
     if (historyl == FALSE)
     hazardf[[i]] = function(t, bl) 99 * to
     else hazardf[[i]] = function(t, history, bl) 99 *
     to
     }
     }
     parametric = numeric()
     k = 0
     for (i in 1:max(auxcounter(statesNumber))) {
     if (is.character(hazardf[[i]])) {
     k = k + 1
     parametric[k] = i
     if (hazardf[[i]] %in% c("Weibull", "multWeibull",
     "Exponential")) {
     hazardf[[i]] <- switch(hazardf[[i]], Weibull = function(t,
     shape, scale, history, bl) rweibull(t, shape,
     scale), multWeibull = function(t, w, shapes,
     scales, history, bl) multPar(t, w, shapes,
     scales), Exponential = function(t, rate, history,
     bl) rexp(t, rate))
     if (!historyl)
     formals(hazardf[[i]])$history <- NULL
     }
     else {
     stop(paste("Transition function for transition",
     i, "not recognized", sep = " "))
     }
     }
     }
     allFunctions = mainFunctions(statesNumber = statesNumber,
     Mu = mu, sigma = sigma, cohortSize = cohortSize, history = historyl,
     hazardf, impossible = c(impossible, fixpar, direct))
     parametric = sort(c(parametric, impossible, direct))
     cohorts <- sapply(1:cohortSize, function(i) {
     if ((i%%report.every == 0) | (i == 1))
     message("Simulating patient:", i)
     print(bl0[i, ])
     historical(gf = allFunctions[[i]], statesNumber = statesNumber,
     parametric = parametric, historyl = historyl, startingState = startingStates[i],
     absorbing = absorbing, bl = bl0[i, ], to = to, sampler.steps = sampler.steps)[[1]]
     })
     print("dimnames")
     dimnames(cohorts) <- list(statesNamesFrom, paste("Patient",
     1:cohortSize))
     print("return(cohorts)")
     return(cohorts)
    }
    <bytecode: 0x3ce4618>
    <environment: namespace:GUIgems>
     --- function search by body ---
    Function createCohorts in namespace GUIgems has this body.
     ----------- END OF FAILURE REPORT --------------
    Error in if (class(sigma) == "transition.structure") { :
     the condition has length > 1
    Calls: simulateCohort -> createCohorts
    Execution halted
Flavor: r-devel-linux-x86_64-debian-clang

Version: 0.1
Check: examples
Result: ERROR
    Running examples in ‘GUIgems-Ex.R’ failed
    The error most likely occurred in:
    
    > base::assign(".ptime", proc.time(), pos = "CheckExEnv")
    > ### Name: mergeStates
    > ### Title: mergeStates
    > ### Aliases: mergeStates
    > ### Keywords: merge mergeStates,
    >
    > ### ** Examples
    >
    >
    > hfNames <- array(rep("Exponential", 16), dim = c(4,4))
    > hfNames[col(hfNames) <= row(hfNames)]<-"NULL"
    > rownames(hfNames) <- as.list(paste("state", 1:4))
    > colnames(hfNames) <- as.list(paste("state", 1:4))
    > M <- makeM(hfNames)
    [1] "state 1" "state 2" "state 3" "state 4"
     to
    from state 1 state 2 state 3 state 4
     state 1 NULL "impossible" "impossible" "impossible"
     state 2 NULL NULL "impossible" "impossible"
     state 3 NULL NULL NULL "impossible"
     state 4 NULL NULL NULL NULL
    > param <- generateParameterMatrix(M)
    > param[[1,2]] <- list(rate = 1)
    > param[[1,3]] <- list(rate = 2)
    > param[[2,3]] <- list(rate = 0.5)
    >
    > param[[1,4]] <- list(rate = 1)
    > param[[2,4]] <- list(rate = 2)
    > param[[3,4]] <- list(rate = 0.5)
    >
    > cohort <- simulateCohort(
    + transitionFunctions = M,
    + parameters = param,
    + cohortSize = 100,
    + to=10)
    [1] "class(parameters)"
    [1] "transition.structure"
    attr(,"package")
    [1] "GUIgems"
     to
    from state 1 state 2 state 3 state 4
     state 1 NULL List,1 List,1 List,1
     state 2 NULL NULL List,1 List,1
     state 3 NULL NULL NULL List,1
     state 4 NULL NULL NULL NULL
     ----------- FAILURE REPORT --------------
     --- failure: the condition has length > 1 ---
     --- srcref ---
    :
     --- package (from environment) ---
    GUIgems
     --- call from context ---
    createCohorts(hazardf = hf, statesNumber = statesNumber, cohortSize = cohortSize,
     mu = parameters.in, sigma = sigma, historyl = historyDep,
     impossible = impossible, fixpar = fixpar, direct = direct,
     bl0 = baseline, startingStates = initialState, absorbing = absorbing,
     to = to, report.every = report.every, sampler.steps = sampler.steps)
     --- call from argument ---
    if (class(sigma) == "transition.structure") {
     if (dim(sigma)[1] != length(unlist(mu)))
     stop("size of parameters and parameterCovariances are inconsistent")
    }
     --- R stacktrace ---
    where 1: createCohorts(hazardf = hf, statesNumber = statesNumber, cohortSize = cohortSize,
     mu = parameters.in, sigma = sigma, historyl = historyDep,
     impossible = impossible, fixpar = fixpar, direct = direct,
     bl0 = baseline, startingStates = initialState, absorbing = absorbing,
     to = to, report.every = report.every, sampler.steps = sampler.steps)
    where 2: simulateCohort(transitionFunctions = M, parameters = param, cohortSize = 100,
     to = 10)
    
     --- value of length: 2 type: logical ---
    [1] FALSE FALSE
     --- function from context ---
    function (hazardf, statesNumber, statesNamesFrom = strsplit((dimnames(hazardf)["from"])[[1]],
     " "), statesNamesTo = statesNamesFrom, cohortSize, mu, sigma = matrix(0,
     nrow = length(unlist(mu)), ncol = length(unlist(mu))), historyl = FALSE,
     startingStates = rep(1, cohortSize), absorbing = cohortSize,
     impossible = NULL, fixpar = NULL, direct = NULL, bl0 = matrix(0,
     nrow = cohortSize), to = 100, report.every, sampler.steps)
    {
     statesNames <- list(from = statesNamesFrom, to = statesNamesTo)
     hazardf <- t(hazardf)[t(auxcounter(statesNumber)) > 0]
     if (length(hazardf) < (statesNumber * (statesNumber - 1)/2)) {
     length(hazardf) <- statesNumber * (statesNumber - 1)/2
     }
     for (tr in 1:length(hazardf)) {
     if (length(hazardf[[tr]]) > 0) {
     if (!is.function(hazardf[[tr]])) {
     if (!hazardf[[tr]] %in% c("Weibull", "multWeibull",
     "Exponential", "impossible") && !is.na(hazardf[[tr]]))
     try(hazardf[[tr]] <- as.function(hazardf[[tr]]))
     }
     }
     }
     mu <- as.list(unlist(t(mu), recursive = FALSE))
     if (length(mu) > 0) {
     mu <- lapply(mu, as.numeric)
     }
     if (class(sigma) == "transition.structure") {
     if (dim(sigma)[1] != length(unlist(mu)))
     stop("size of parameters and parameterCovariances are inconsistent")
     }
     if (length(startingStates) == 1)
     rep(startingStates, cohortSize)
     if (cohortSize > 1) {
     try(bl0 <- as.matrix(bl0))
     }
     else if (is.null(dim(bl0))) {
     try(bl0 <- t(as.matrix(bl0)))
     }
     if (nrow(bl0) != cohortSize)
     warning("baseline is not of the right dimension")
     for (i in 1:length(hazardf)) {
     if (is.element(i, impossible)) {
     if (historyl == FALSE)
     hazardf[[i]] = function(t, bl) 99 * to
     else hazardf[[i]] = function(t, history, bl) 99 *
     to
     }
     }
     parametric = numeric()
     k = 0
     for (i in 1:max(auxcounter(statesNumber))) {
     if (is.character(hazardf[[i]])) {
     k = k + 1
     parametric[k] = i
     if (hazardf[[i]] %in% c("Weibull", "multWeibull",
     "Exponential")) {
     hazardf[[i]] <- switch(hazardf[[i]], Weibull = function(t,
     shape, scale, history, bl) rweibull(t, shape,
     scale), multWeibull = function(t, w, shapes,
     scales, history, bl) multPar(t, w, shapes,
     scales), Exponential = function(t, rate, history,
     bl) rexp(t, rate))
     if (!historyl)
     formals(hazardf[[i]])$history <- NULL
     }
     else {
     stop(paste("Transition function for transition",
     i, "not recognized", sep = " "))
     }
     }
     }
     allFunctions = mainFunctions(statesNumber = statesNumber,
     Mu = mu, sigma = sigma, cohortSize = cohortSize, history = historyl,
     hazardf, impossible = c(impossible, fixpar, direct))
     parametric = sort(c(parametric, impossible, direct))
     cohorts <- sapply(1:cohortSize, function(i) {
     if ((i%%report.every == 0) | (i == 1))
     message("Simulating patient:", i)
     print(bl0[i, ])
     historical(gf = allFunctions[[i]], statesNumber = statesNumber,
     parametric = parametric, historyl = historyl, startingState = startingStates[i],
     absorbing = absorbing, bl = bl0[i, ], to = to, sampler.steps = sampler.steps)[[1]]
     })
     print("dimnames")
     dimnames(cohorts) <- list(statesNamesFrom, paste("Patient",
     1:cohortSize))
     print("return(cohorts)")
     return(cohorts)
    }
    <bytecode: 0x5571d5a52690>
    <environment: namespace:GUIgems>
     --- function search by body ---
    Function createCohorts in namespace GUIgems has this body.
     ----------- END OF FAILURE REPORT --------------
    Error in if (class(sigma) == "transition.structure") { :
     the condition has length > 1
    Calls: simulateCohort -> createCohorts
    Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc

Version: 0.1
Check: dependencies in R code
Result: NOTE
    Namespace in Imports field not imported from: ‘stringr’
     All declared Imports should be used.
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-patched-solaris-x86

Version: 0.1
Check: examples
Result: ERROR
    Running examples in ‘GUIgems-Ex.R’ failed
    The error most likely occurred in:
    
    > ### Name: mergeStates
    > ### Title: mergeStates
    > ### Aliases: mergeStates
    > ### Keywords: merge mergeStates,
    >
    > ### ** Examples
    >
    >
    > hfNames <- array(rep("Exponential", 16), dim = c(4,4))
    > hfNames[col(hfNames) <= row(hfNames)]<-"NULL"
    > rownames(hfNames) <- as.list(paste("state", 1:4))
    > colnames(hfNames) <- as.list(paste("state", 1:4))
    > M <- makeM(hfNames)
    [1] "state 1" "state 2" "state 3" "state 4"
     to
    from state 1 state 2 state 3 state 4
     state 1 NULL "impossible" "impossible" "impossible"
     state 2 NULL NULL "impossible" "impossible"
     state 3 NULL NULL NULL "impossible"
     state 4 NULL NULL NULL NULL
    > param <- generateParameterMatrix(M)
    > param[[1,2]] <- list(rate = 1)
    > param[[1,3]] <- list(rate = 2)
    > param[[2,3]] <- list(rate = 0.5)
    >
    > param[[1,4]] <- list(rate = 1)
    > param[[2,4]] <- list(rate = 2)
    > param[[3,4]] <- list(rate = 0.5)
    >
    > cohort <- simulateCohort(
    + transitionFunctions = M,
    + parameters = param,
    + cohortSize = 100,
    + to=10)
    [1] "class(parameters)"
    [1] "transition.structure"
    attr(,"package")
    [1] "GUIgems"
     to
    from state 1 state 2 state 3 state 4
     state 1 NULL List,1 List,1 List,1
     state 2 NULL NULL List,1 List,1
     state 3 NULL NULL NULL List,1
     state 4 NULL NULL NULL NULL
     ----------- FAILURE REPORT --------------
     --- failure: the condition has length > 1 ---
     --- srcref ---
    :
     --- package (from environment) ---
    GUIgems
     --- call from context ---
    createCohorts(hazardf = hf, statesNumber = statesNumber, cohortSize = cohortSize,
     mu = parameters.in, sigma = sigma, historyl = historyDep,
     impossible = impossible, fixpar = fixpar, direct = direct,
     bl0 = baseline, startingStates = initialState, absorbing = absorbing,
     to = to, report.every = report.every, sampler.steps = sampler.steps)
     --- call from argument ---
    if (class(sigma) == "transition.structure") {
     if (dim(sigma)[1] != length(unlist(mu)))
     stop("size of parameters and parameterCovariances are inconsistent")
    }
     --- R stacktrace ---
    where 1: createCohorts(hazardf = hf, statesNumber = statesNumber, cohortSize = cohortSize,
     mu = parameters.in, sigma = sigma, historyl = historyDep,
     impossible = impossible, fixpar = fixpar, direct = direct,
     bl0 = baseline, startingStates = initialState, absorbing = absorbing,
     to = to, report.every = report.every, sampler.steps = sampler.steps)
    where 2: simulateCohort(transitionFunctions = M, parameters = param, cohortSize = 100,
     to = 10)
    
     --- value of length: 2 type: logical ---
    [1] FALSE FALSE
     --- function from context ---
    function (hazardf, statesNumber, statesNamesFrom = strsplit((dimnames(hazardf)["from"])[[1]],
     " "), statesNamesTo = statesNamesFrom, cohortSize, mu, sigma = matrix(0,
     nrow = length(unlist(mu)), ncol = length(unlist(mu))), historyl = FALSE,
     startingStates = rep(1, cohortSize), absorbing = cohortSize,
     impossible = NULL, fixpar = NULL, direct = NULL, bl0 = matrix(0,
     nrow = cohortSize), to = 100, report.every, sampler.steps)
    {
     statesNames <- list(from = statesNamesFrom, to = statesNamesTo)
     hazardf <- t(hazardf)[t(auxcounter(statesNumber)) > 0]
     if (length(hazardf) < (statesNumber * (statesNumber - 1)/2)) {
     length(hazardf) <- statesNumber * (statesNumber - 1)/2
     }
     for (tr in 1:length(hazardf)) {
     if (length(hazardf[[tr]]) > 0) {
     if (!is.function(hazardf[[tr]])) {
     if (!hazardf[[tr]] %in% c("Weibull", "multWeibull",
     "Exponential", "impossible") && !is.na(hazardf[[tr]]))
     try(hazardf[[tr]] <- as.function(hazardf[[tr]]))
     }
     }
     }
     mu <- as.list(unlist(t(mu), recursive = FALSE))
     if (length(mu) > 0) {
     mu <- lapply(mu, as.numeric)
     }
     if (class(sigma) == "transition.structure") {
     if (dim(sigma)[1] != length(unlist(mu)))
     stop("size of parameters and parameterCovariances are inconsistent")
     }
     if (length(startingStates) == 1)
     rep(startingStates, cohortSize)
     if (cohortSize > 1) {
     try(bl0 <- as.matrix(bl0))
     }
     else if (is.null(dim(bl0))) {
     try(bl0 <- t(as.matrix(bl0)))
     }
     if (nrow(bl0) != cohortSize)
     warning("baseline is not of the right dimension")
     for (i in 1:length(hazardf)) {
     if (is.element(i, impossible)) {
     if (historyl == FALSE)
     hazardf[[i]] = function(t, bl) 99 * to
     else hazardf[[i]] = function(t, history, bl) 99 *
     to
     }
     }
     parametric = numeric()
     k = 0
     for (i in 1:max(auxcounter(statesNumber))) {
     if (is.character(hazardf[[i]])) {
     k = k + 1
     parametric[k] = i
     if (hazardf[[i]] %in% c("Weibull", "multWeibull",
     "Exponential")) {
     hazardf[[i]] <- switch(hazardf[[i]], Weibull = function(t,
     shape, scale, history, bl) rweibull(t, shape,
     scale), multWeibull = function(t, w, shapes,
     scales, history, bl) multPar(t, w, shapes,
     scales), Exponential = function(t, rate, history,
     bl) rexp(t, rate))
     if (!historyl)
     formals(hazardf[[i]])$history <- NULL
     }
     else {
     stop(paste("Transition function for transition",
     i, "not recognized", sep = " "))
     }
     }
     }
     allFunctions = mainFunctions(statesNumber = statesNumber,
     Mu = mu, sigma = sigma, cohortSize = cohortSize, history = historyl,
     hazardf, impossible = c(impossible, fixpar, direct))
     parametric = sort(c(parametric, impossible, direct))
     cohorts <- sapply(1:cohortSize, function(i) {
     if ((i%%report.every == 0) | (i == 1))
     message("Simulating patient:", i)
     print(bl0[i, ])
     historical(gf = allFunctions[[i]], statesNumber = statesNumber,
     parametric = parametric, historyl = historyl, startingState = startingStates[i],
     absorbing = absorbing, bl = bl0[i, ], to = to, sampler.steps = sampler.steps)[[1]]
     })
     print("dimnames")
     dimnames(cohorts) <- list(statesNamesFrom, paste("Patient",
     1:cohortSize))
     print("return(cohorts)")
     return(cohorts)
    }
    <bytecode: 0xd8554c0>
    <environment: namespace:GUIgems>
     --- function search by body ---
    Function createCohorts in namespace GUIgems has this body.
     ----------- END OF FAILURE REPORT --------------
    Error in if (class(sigma) == "transition.structure") { :
     the condition has length > 1
    Calls: simulateCohort -> createCohorts
    Execution halted
Flavor: r-devel-linux-x86_64-fedora-clang

Version: 0.1
Check: examples
Result: ERROR
    Running examples in ‘GUIgems-Ex.R’ failed
    The error most likely occurred in:
    
    > ### Name: mergeStates
    > ### Title: mergeStates
    > ### Aliases: mergeStates
    > ### Keywords: merge mergeStates,
    >
    > ### ** Examples
    >
    >
    > hfNames <- array(rep("Exponential", 16), dim = c(4,4))
    > hfNames[col(hfNames) <= row(hfNames)]<-"NULL"
    > rownames(hfNames) <- as.list(paste("state", 1:4))
    > colnames(hfNames) <- as.list(paste("state", 1:4))
    > M <- makeM(hfNames)
    [1] "state 1" "state 2" "state 3" "state 4"
     to
    from state 1 state 2 state 3 state 4
     state 1 NULL "impossible" "impossible" "impossible"
     state 2 NULL NULL "impossible" "impossible"
     state 3 NULL NULL NULL "impossible"
     state 4 NULL NULL NULL NULL
    > param <- generateParameterMatrix(M)
    > param[[1,2]] <- list(rate = 1)
    > param[[1,3]] <- list(rate = 2)
    > param[[2,3]] <- list(rate = 0.5)
    >
    > param[[1,4]] <- list(rate = 1)
    > param[[2,4]] <- list(rate = 2)
    > param[[3,4]] <- list(rate = 0.5)
    >
    > cohort <- simulateCohort(
    + transitionFunctions = M,
    + parameters = param,
    + cohortSize = 100,
    + to=10)
    [1] "class(parameters)"
    [1] "transition.structure"
    attr(,"package")
    [1] "GUIgems"
     to
    from state 1 state 2 state 3 state 4
     state 1 NULL List,1 List,1 List,1
     state 2 NULL NULL List,1 List,1
     state 3 NULL NULL NULL List,1
     state 4 NULL NULL NULL NULL
     ----------- FAILURE REPORT --------------
     --- failure: the condition has length > 1 ---
     --- srcref ---
    :
     --- package (from environment) ---
    GUIgems
     --- call from context ---
    createCohorts(hazardf = hf, statesNumber = statesNumber, cohortSize = cohortSize,
     mu = parameters.in, sigma = sigma, historyl = historyDep,
     impossible = impossible, fixpar = fixpar, direct = direct,
     bl0 = baseline, startingStates = initialState, absorbing = absorbing,
     to = to, report.every = report.every, sampler.steps = sampler.steps)
     --- call from argument ---
    if (class(sigma) == "transition.structure") {
     if (dim(sigma)[1] != length(unlist(mu)))
     stop("size of parameters and parameterCovariances are inconsistent")
    }
     --- R stacktrace ---
    where 1: createCohorts(hazardf = hf, statesNumber = statesNumber, cohortSize = cohortSize,
     mu = parameters.in, sigma = sigma, historyl = historyDep,
     impossible = impossible, fixpar = fixpar, direct = direct,
     bl0 = baseline, startingStates = initialState, absorbing = absorbing,
     to = to, report.every = report.every, sampler.steps = sampler.steps)
    where 2: simulateCohort(transitionFunctions = M, parameters = param, cohortSize = 100,
     to = 10)
    
     --- value of length: 2 type: logical ---
    [1] FALSE FALSE
     --- function from context ---
    function (hazardf, statesNumber, statesNamesFrom = strsplit((dimnames(hazardf)["from"])[[1]],
     " "), statesNamesTo = statesNamesFrom, cohortSize, mu, sigma = matrix(0,
     nrow = length(unlist(mu)), ncol = length(unlist(mu))), historyl = FALSE,
     startingStates = rep(1, cohortSize), absorbing = cohortSize,
     impossible = NULL, fixpar = NULL, direct = NULL, bl0 = matrix(0,
     nrow = cohortSize), to = 100, report.every, sampler.steps)
    {
     statesNames <- list(from = statesNamesFrom, to = statesNamesTo)
     hazardf <- t(hazardf)[t(auxcounter(statesNumber)) > 0]
     if (length(hazardf) < (statesNumber * (statesNumber - 1)/2)) {
     length(hazardf) <- statesNumber * (statesNumber - 1)/2
     }
     for (tr in 1:length(hazardf)) {
     if (length(hazardf[[tr]]) > 0) {
     if (!is.function(hazardf[[tr]])) {
     if (!hazardf[[tr]] %in% c("Weibull", "multWeibull",
     "Exponential", "impossible") && !is.na(hazardf[[tr]]))
     try(hazardf[[tr]] <- as.function(hazardf[[tr]]))
     }
     }
     }
     mu <- as.list(unlist(t(mu), recursive = FALSE))
     if (length(mu) > 0) {
     mu <- lapply(mu, as.numeric)
     }
     if (class(sigma) == "transition.structure") {
     if (dim(sigma)[1] != length(unlist(mu)))
     stop("size of parameters and parameterCovariances are inconsistent")
     }
     if (length(startingStates) == 1)
     rep(startingStates, cohortSize)
     if (cohortSize > 1) {
     try(bl0 <- as.matrix(bl0))
     }
     else if (is.null(dim(bl0))) {
     try(bl0 <- t(as.matrix(bl0)))
     }
     if (nrow(bl0) != cohortSize)
     warning("baseline is not of the right dimension")
     for (i in 1:length(hazardf)) {
     if (is.element(i, impossible)) {
     if (historyl == FALSE)
     hazardf[[i]] = function(t, bl) 99 * to
     else hazardf[[i]] = function(t, history, bl) 99 *
     to
     }
     }
     parametric = numeric()
     k = 0
     for (i in 1:max(auxcounter(statesNumber))) {
     if (is.character(hazardf[[i]])) {
     k = k + 1
     parametric[k] = i
     if (hazardf[[i]] %in% c("Weibull", "multWeibull",
     "Exponential")) {
     hazardf[[i]] <- switch(hazardf[[i]], Weibull = function(t,
     shape, scale, history, bl) rweibull(t, shape,
     scale), multWeibull = function(t, w, shapes,
     scales, history, bl) multPar(t, w, shapes,
     scales), Exponential = function(t, rate, history,
     bl) rexp(t, rate))
     if (!historyl)
     formals(hazardf[[i]])$history <- NULL
     }
     else {
     stop(paste("Transition function for transition",
     i, "not recognized", sep = " "))
     }
     }
     }
     allFunctions = mainFunctions(statesNumber = statesNumber,
     Mu = mu, sigma = sigma, cohortSize = cohortSize, history = historyl,
     hazardf, impossible = c(impossible, fixpar, direct))
     parametric = sort(c(parametric, impossible, direct))
     cohorts <- sapply(1:cohortSize, function(i) {
     if ((i%%report.every == 0) | (i == 1))
     message("Simulating patient:", i)
     print(bl0[i, ])
     historical(gf = allFunctions[[i]], statesNumber = statesNumber,
     parametric = parametric, historyl = historyl, startingState = startingStates[i],
     absorbing = absorbing, bl = bl0[i, ], to = to, sampler.steps = sampler.steps)[[1]]
     })
     print("dimnames")
     dimnames(cohorts) <- list(statesNamesFrom, paste("Patient",
     1:cohortSize))
     print("return(cohorts)")
     return(cohorts)
    }
    <bytecode: 0xc9d78c0>
    <environment: namespace:GUIgems>
     --- function search by body ---
    Function createCohorts in namespace GUIgems has this body.
     ----------- END OF FAILURE REPORT --------------
    Error in if (class(sigma) == "transition.structure") { :
     the condition has length > 1
    Calls: simulateCohort -> createCohorts
    Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc

Version: 0.1
Check: package dependencies
Result: ERROR
    Package required but not available: ‘rpanel’
    
    See section ‘The DESCRIPTION file’ in the ‘Writing R Extensions’
    manual.
Flavors: r-release-osx-x86_64, r-oldrel-osx-x86_64