Running ‘testthat.R’ [17s/26s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
  > library(testthat)
  > library(nlmixr2extra)
  > 
  > test_check("nlmixr2extra")
  
   *** caught segfault ***
  address 0x18, cause 'memory not mapped'
  
  Traceback:
   1: objective(.par, ...)
   2: stats::nlminb(start = par, objective = fn, gradient = gr, hessian = NULL,     control = .ctl, lower = lower, upper = upper)
   3: (function (par, fn, gr, lower = -Inf, upper = Inf, control = list(),     ...) {    .ctl <- control    .ctl <- .ctl[names(.ctl) %in% c("eval.max", "iter.max", "trace",         "abs.tol", "rel.tol", "x.tol", "xf.tol", "step.min",         "step.max", "sing.tol", "scale.inti", "diff.g")]    .ctl$trace <- 0    .ret <- stats::nlminb(start = par, objective = fn, gradient = gr,         hessian = NULL, control = .ctl, lower = lower, upper = upper)    .ret$x <- .ret$par    return(.ret)})(par = c(-1, -0.633333333333333, 1, -0.833333333333333, -0.542520422355001, -0.39919989679531, -0.114480393307385), fn = function (theta) {    .Call(`_nlmixr2est_foceiOuterF`, theta)}, gr = function (theta) {    .Call(`_nlmixr2est_foceiOuterG`, theta)}, lower = c(-Inf, -Inf, -Inf, -2.83333163034348, -0.873779194190821, -0.730458752094879, -0.44573935454913), upper = c(Inf, Inf, Inf, Inf, 1.61975587753649, 1.76307631963243, 2.04779571717818), control = list(    maxOuterIterations = 5000L, maxInnerIterations = 1000L, n1qn1nsim = 10001L,     print = 0L, lbfgsLmm = 7L, lbfgsPgtol = 0, lbfgsFactr = 450359962737.05,     scaleTo = 1, epsilon = 1e-04, derivEps = c(2.98023223876953e-07,     2.98023223876953e-07), derivMethod = 3L, covDerivMethod = 1L,     covMethod = 1L, centralDerivEps = c(2.98023223876953e-07,     2.98023223876953e-07), eigen = 1L, addPosthoc = 1L, diagXform = "sqrt",     sumProd = FALSE, optExpression = TRUE, outerOpt = -1L, ci = 0.95,     sigdig = 3, sigdigTable = 3, scaleObjective = 0, useColor = FALSE,     boundTol = 0.05, calcTables = TRUE, printNcol = 4L, noAbort = 1L,     interaction = 1L, cholSEtol = 6.05545445239334e-06, hessEps = 6.05545445239334e-06,     cholAccept = 0.001, resetEtaSize = 1.43953147093846, resetThetaSize = 1.95996398454005,     resetThetaFinalSize = 1.43953147093846, diagOmegaBoundUpper = 5,     diagOmegaBoundLower = 100, cholSEOpt = 0L, cholSECov = 0L,     fo = 0L, covTryHarder = 0L, outerOptFun = function (par,         fn, gr, lower = -Inf, upper = Inf, control = list(),         ...)     {        .ctl <- control        .ctl <- .ctl[names(.ctl) %in% c("eval.max", "iter.max",             "trace", "abs.tol", "rel.tol", "x.tol", "xf.tol",             "step.min", "step.max", "sing.tol", "scale.inti",             "diff.g")]        .ctl$trace <- 0        .ret <- stats::nlminb(start = par, objective = fn, gradient = gr,             hessian = NULL, control = .ctl, lower = lower, upper = upper)        .ret$x <- .ret$par        return(.ret)    }, rhobeg = 0.2, rhoend = 1e-04, npt = NULL, rel.tol = 1e-04,     x.tol = 1e-04, eval.max = 4000, iter.max = 2000, innerOpt = 1L,     abstol = 1e-04, reltol = 1e-04, derivSwitchTol = 2e-04, resetHessianAndEta = 0L,     stateTrim = Inf, gillK = 10L, gillKcov = 10L, gillRtol = 1.49011611938477e-08,     gillStep = 4, gillStepCov = 2, scaleType = 2L, normType = 1L,     scaleC = NULL, scaleCmin = 1e-05, scaleCmax = 1e+05, scaleC0 = 1e+05,     outerOptTxt = "nlminb", rmatNorm = 1L, smatNorm = 1L, covGillF = 1L,     optGillF = 1L, gillFtol = 0, gillFtolCov = 0, covSmall = 1e-05,     adjLik = TRUE, gradTrim = Inf, gradCalcCentralSmall = 1e-04,     gradCalcCentralLarge = 10000, etaNudge = 1.13158573407617,     etaNudge2 = 1.51818157425799, maxOdeRecalc = 5L, odeRecalcFactor = 3.16227766016838,     nRetries = 3, seed = 42, resetThetaCheckPer = 0.1, etaMat = NULL,     repeatGillMax = 3L, stickyRecalcN = 5L, eventFD = 1.49011611938477e-08,     eventType = 1L, gradProgressOfvTime = 10, addProp = "combined2",     badSolveObjfAdj = 100, compress = TRUE, rxControl = list(        scale = NULL, method = c(liblsoda = 2L), atol = c(5e-06,         5e-06, 1.58113883008419e-05, 1.58113883008419e-05, 1.58113883008419e-05,         1.58113883008419e-05, 1.58113883008419e-05, 1.58113883008419e-05        ), rtol = c(5e-06, 5e-06, 1.58113883008419e-05, 1.58113883008419e-05,         1.58113883008419e-05, 1.58113883008419e-05, 1.58113883008419e-05,         1.58113883008419e-05), maxsteps = 500000L, hmin = 0,         hmax = NA_real_, hini = 0, maxordn = 12L, maxords = 5L,         covsInterpolation = c(locf = 1L), addCov = TRUE, returnType = c(rxSolve = 0L),         sigma = NULL, sigmaDf = NULL, nCoresRV = 1L, sigmaIsChol = FALSE,         sigmaSeparation = "auto", sigmaXform = c(identity = 4L),         nDisplayProgress = 10000L, amountUnits = NA_character_,         timeUnits = "hours", addDosing = FALSE, stateTrim = Inf,         updateObject = FALSE, omega = NULL, omegaDf = NULL, omegaIsChol = FALSE,         omegaSeparation = "auto", omegaXform = c(variance = 6L),         nSub = 1L, thetaMat = NULL, thetaDf = NULL, thetaIsChol = FALSE,         nStud = 1L, dfSub = 0, dfObs = 0, seed = NULL, nsim = NULL,         minSS = 10L, maxSS = 1000L, strictSS = 1L, infSSstep = 12,         istateReset = TRUE, subsetNonmem = TRUE, hmaxSd = 0,         maxAtolRtolFactor = 0.1, from = NULL, to = NULL, by = NULL,         length.out = NULL, iCov = NULL, keep = NULL, keepF = character(0),         drop = NULL, warnDrop = TRUE, omegaLower = -Inf, omegaUpper = Inf,         sigmaLower = -Inf, sigmaUpper = Inf, thetaLower = -Inf,         thetaUpper = Inf, indLinPhiM = 0L, indLinPhiTol = 1e-07,         indLinMatExpType = c(expokit = 2L), indLinMatExpOrder = 6L,         idFactor = TRUE, mxhnil = 0L, hmxi = 0, warnIdSort = TRUE,         ssAtol = c(5e-04, 5e-04, 0.00210848251714291, 0.00210848251714291,         0.00210848251714291, 0.00210848251714291, 0.00210848251714291,         0.00210848251714291), ssRtol = c(5e-04, 5e-04, 0.00210848251714291,         0.00210848251714291, 0.00210848251714291, 0.00210848251714291,         0.00210848251714291, 0.00210848251714291), safeZero = 1L,         sumType = c(pairwise = 1L), prodType = c(`long double` = 1L),         sensType = c(advan = 4L), linDiff = c(tlag = 1.5e-05,         f = 1.5e-05, rate = 1.5e-05, dur = 1.5e-05, tlag2 = 1.5e-05,         f2 = 1.5e-05, rate2 = 1.5e-05, dur2 = 1.5e-05), linDiffCentral = c(tlag = TRUE,         f = TRUE, rate = TRUE, dur = TRUE, tlag2 = TRUE, f2 = TRUE,         rate2 = TRUE, dur2 = TRUE), resample = NULL, resampleID = TRUE,         maxwhile = 100000L, cores = 1L, atolSens = 1.58113883008419e-05,         rtolSens = 1.58113883008419e-05, ssAtolSens = 0.00210848251714291,         ssRtolSens = 0.00210848251714291, simVariability = NA,         nLlikAlloc = NULL, useStdPow = 0L), genRxControl = TRUE,     skipCov = NULL, fallbackFD = FALSE, foceiMuRef = c(0L, 0L,     0L), predNeq = 2L, nfixed = 0L, nomega = 3L, neta = 3L, ntheta = 4L,     nF = 0, printTop = TRUE))
   4: evalq((function (par, fn, gr, lower = -Inf, upper = Inf, control = list(),     ...) {    .ctl <- control    .ctl <- .ctl[names(.ctl) %in% c("eval.max", "iter.max", "trace",         "abs.tol", "rel.tol", "x.tol", "xf.tol", "step.min",         "step.max", "sing.tol", "scale.inti", "diff.g")]    .ctl$trace <- 0    .ret <- stats::nlminb(start = par, objective = fn, gradient = gr,         hessian = NULL, control = .ctl, lower = lower, upper = upper)    .ret$x <- .ret$par    return(.ret)})(par = c(-1, -0.633333333333333, 1, -0.833333333333333, -0.542520422355001, -0.39919989679531, -0.114480393307385), fn = function (theta) {    .Call(`_nlmixr2est_foceiOuterF`, theta)}, gr = function (theta) {    .Call(`_nlmixr2est_foceiOuterG`, theta)}, lower = c(-Inf, -Inf, -Inf, -2.83333163034348, -0.873779194190821, -0.730458752094879, -0.44573935454913), upper = c(Inf, Inf, Inf, Inf, 1.61975587753649, 1.76307631963243, 2.04779571717818), control = list(    maxOuterIterations = 5000L, maxInnerIterations = 1000L, n1qn1nsim = 10001L,     print = 0L, lbfgsLmm = 7L, lbfgsPgtol = 0, lbfgsFactr = 450359962737.05,     scaleTo = 1, epsilon = 1e-04, derivEps = c(2.98023223876953e-07,     2.98023223876953e-07), derivMethod = 3L, covDerivMethod = 1L,     covMethod = 1L, centralDerivEps = c(2.98023223876953e-07,     2.98023223876953e-07), eigen = 1L, addPosthoc = 1L, diagXform = "sqrt",     sumProd = FALSE, optExpression = TRUE, outerOpt = -1L, ci = 0.95,     sigdig = 3, sigdigTable = 3, scaleObjective = 0, useColor = FALSE,     boundTol = 0.05, calcTables = TRUE, printNcol = 4L, noAbort = 1L,     interaction = 1L, cholSEtol = 6.05545445239334e-06, hessEps = 6.05545445239334e-06,     cholAccept = 0.001, resetEtaSize = 1.43953147093846, resetThetaSize = 1.95996398454005,     resetThetaFinalSize = 1.43953147093846, diagOmegaBoundUpper = 5,     diagOmegaBoundLower = 100, cholSEOpt = 0L, cholSECov = 0L,     fo = 0L, covTryHarder = 0L, outerOptFun = function (par,         fn, gr, lower = -Inf, upper = Inf, control = list(),         ...)     {        .ctl <- control        .ctl <- .ctl[names(.ctl) %in% c("eval.max", "iter.max",             "trace", "abs.tol", "rel.tol", "x.tol", "xf.tol",             "step.min", "step.max", "sing.tol", "scale.inti",             "diff.g")]        .ctl$trace <- 0        .ret <- stats::nlminb(start = par, objective = fn, gradient = gr,             hessian = NULL, control = .ctl, lower = lower, upper = upper)        .ret$x <- .ret$par        return(.ret)    }, rhobeg = 0.2, rhoend = 1e-04, npt = NULL, rel.tol = 1e-04,     x.tol = 1e-04, eval.max = 4000, iter.max = 2000, innerOpt = 1L,     abstol = 1e-04, reltol = 1e-04, derivSwitchTol = 2e-04, resetHessianAndEta = 0L,     stateTrim = Inf, gillK = 10L, gillKcov = 10L, gillRtol = 1.49011611938477e-08,     gillStep = 4, gillStepCov = 2, scaleType = 2L, normType = 1L,     scaleC = NULL, scaleCmin = 1e-05, scaleCmax = 1e+05, scaleC0 = 1e+05,     outerOptTxt = "nlminb", rmatNorm = 1L, smatNorm = 1L, covGillF = 1L,     optGillF = 1L, gillFtol = 0, gillFtolCov = 0, covSmall = 1e-05,     adjLik = TRUE, gradTrim = Inf, gradCalcCentralSmall = 1e-04,     gradCalcCentralLarge = 10000, etaNudge = 1.13158573407617,     etaNudge2 = 1.51818157425799, maxOdeRecalc = 5L, odeRecalcFactor = 3.16227766016838,     nRetries = 3, seed = 42, resetThetaCheckPer = 0.1, etaMat = NULL,     repeatGillMax = 3L, stickyRecalcN = 5L, eventFD = 1.49011611938477e-08,     eventType = 1L, gradProgressOfvTime = 10, addProp = "combined2",     badSolveObjfAdj = 100, compress = TRUE, rxControl = list(        scale = NULL, method = c(liblsoda = 2L), atol = c(5e-06,         5e-06, 1.58113883008419e-05, 1.58113883008419e-05, 1.58113883008419e-05,         1.58113883008419e-05, 1.58113883008419e-05, 1.58113883008419e-05        ), rtol = c(5e-06, 5e-06, 1.58113883008419e-05, 1.58113883008419e-05,         1.58113883008419e-05, 1.58113883008419e-05, 1.58113883008419e-05,         1.58113883008419e-05), maxsteps = 500000L, hmin = 0,         hmax = NA_real_, hini = 0, maxordn = 12L, maxords = 5L,         covsInterpolation = c(locf = 1L), addCov = TRUE, returnType = c(rxSolve = 0L),         sigma = NULL, sigmaDf = NULL, nCoresRV = 1L, sigmaIsChol = FALSE,         sigmaSeparation = "auto", sigmaXform = c(identity = 4L),         nDisplayProgress = 10000L, amountUnits = NA_character_,         timeUnits = "hours", addDosing = FALSE, stateTrim = Inf,         updateObject = FALSE, omega = NULL, omegaDf = NULL, omegaIsChol = FALSE,         omegaSeparation = "auto", omegaXform = c(variance = 6L),         nSub = 1L, thetaMat = NULL, thetaDf = NULL, thetaIsChol = FALSE,         nStud = 1L, dfSub = 0, dfObs = 0, seed = NULL, nsim = NULL,         minSS = 10L, maxSS = 1000L, strictSS = 1L, infSSstep = 12,         istateReset = TRUE, subsetNonmem = TRUE, hmaxSd = 0,         maxAtolRtolFactor = 0.1, from = NULL, to = NULL, by = NULL,         length.out = NULL, iCov = NULL, keep = NULL, keepF = character(0),         drop = NULL, warnDrop = TRUE, omegaLower = -Inf, omegaUpper = Inf,         sigmaLower = -Inf, sigmaUpper = Inf, thetaLower = -Inf,         thetaUpper = Inf, indLinPhiM = 0L, indLinPhiTol = 1e-07,         indLinMatExpType = c(expokit = 2L), indLinMatExpOrder = 6L,         idFactor = TRUE, mxhnil = 0L, hmxi = 0, warnIdSort = TRUE,         ssAtol = c(5e-04, 5e-04, 0.00210848251714291, 0.00210848251714291,         0.00210848251714291, 0.00210848251714291, 0.00210848251714291,         0.00210848251714291), ssRtol = c(5e-04, 5e-04, 0.00210848251714291,         0.00210848251714291, 0.00210848251714291, 0.00210848251714291,         0.00210848251714291, 0.00210848251714291), safeZero = 1L,         sumType = c(pairwise = 1L), prodType = c(`long double` = 1L),         sensType = c(advan = 4L), linDiff = c(tlag = 1.5e-05,         f = 1.5e-05, rate = 1.5e-05, dur = 1.5e-05, tlag2 = 1.5e-05,         f2 = 1.5e-05, rate2 = 1.5e-05, dur2 = 1.5e-05), linDiffCentral = c(tlag = TRUE,         f = TRUE, rate = TRUE, dur = TRUE, tlag2 = TRUE, f2 = TRUE,         rate2 = TRUE, dur2 = TRUE), resample = NULL, resampleID = TRUE,         maxwhile = 100000L, cores = 1L, atolSens = 1.58113883008419e-05,         rtolSens = 1.58113883008419e-05, ssAtolSens = 0.00210848251714291,         ssRtolSens = 0.00210848251714291, simVariability = NA,         nLlikAlloc = NULL, useStdPow = 0L), genRxControl = TRUE,     skipCov = NULL, fallbackFD = FALSE, foceiMuRef = c(0L, 0L,     0L), predNeq = 2L, nfixed = 0L, nomega = 3L, neta = 3L, ntheta = 4L,     nF = 0, printTop = TRUE)), <environment>)
   5: evalq((function (par, fn, gr, lower = -Inf, upper = Inf, control = list(),     ...) {    .ctl <- control    .ctl <- .ctl[names(.ctl) %in% c("eval.max", "iter.max", "trace",         "abs.tol", "rel.tol", "x.tol", "xf.tol", "step.min",         "step.max", "sing.tol", "scale.inti", "diff.g")]    .ctl$trace <- 0    .ret <- stats::nlminb(start = par, objective = fn, gradient = gr,         hessian = NULL, control = .ctl, lower = lower, upper = upper)    .ret$x <- .ret$par    return(.ret)})(par = c(-1, -0.633333333333333, 1, -0.833333333333333, -0.542520422355001, -0.39919989679531, -0.114480393307385), fn = function (theta) {    .Call(`_nlmixr2est_foceiOuterF`, theta)}, gr = function (theta) {    .Call(`_nlmixr2est_foceiOuterG`, theta)}, lower = c(-Inf, -Inf, -Inf, -2.83333163034348, -0.873779194190821, -0.730458752094879, -0.44573935454913), upper = c(Inf, Inf, Inf, Inf, 1.61975587753649, 1.76307631963243, 2.04779571717818), control = list(    maxOuterIterations = 5000L, maxInnerIterations = 1000L, n1qn1nsim = 10001L,     print = 0L, lbfgsLmm = 7L, lbfgsPgtol = 0, lbfgsFactr = 450359962737.05,     scaleTo = 1, epsilon = 1e-04, derivEps = c(2.98023223876953e-07,     2.98023223876953e-07), derivMethod = 3L, covDerivMethod = 1L,     covMethod = 1L, centralDerivEps = c(2.98023223876953e-07,     2.98023223876953e-07), eigen = 1L, addPosthoc = 1L, diagXform = "sqrt",     sumProd = FALSE, optExpression = TRUE, outerOpt = -1L, ci = 0.95,     sigdig = 3, sigdigTable = 3, scaleObjective = 0, useColor = FALSE,     boundTol = 0.05, calcTables = TRUE, printNcol = 4L, noAbort = 1L,     interaction = 1L, cholSEtol = 6.05545445239334e-06, hessEps = 6.05545445239334e-06,     cholAccept = 0.001, resetEtaSize = 1.43953147093846, resetThetaSize = 1.95996398454005,     resetThetaFinalSize = 1.43953147093846, diagOmegaBoundUpper = 5,     diagOmegaBoundLower = 100, cholSEOpt = 0L, cholSECov = 0L,     fo = 0L, covTryHarder = 0L, outerOptFun = function (par,         fn, gr, lower = -Inf, upper = Inf, control = list(),         ...)     {        .ctl <- control        .ctl <- .ctl[names(.ctl) %in% c("eval.max", "iter.max",             "trace", "abs.tol", "rel.tol", "x.tol", "xf.tol",             "step.min", "step.max", "sing.tol", "scale.inti",             "diff.g")]        .ctl$trace <- 0        .ret <- stats::nlminb(start = par, objective = fn, gradient = gr,             hessian = NULL, control = .ctl, lower = lower, upper = upper)        .ret$x <- .ret$par        return(.ret)    }, rhobeg = 0.2, rhoend = 1e-04, npt = NULL, rel.tol = 1e-04,     x.tol = 1e-04, eval.max = 4000, iter.max = 2000, innerOpt = 1L,     abstol = 1e-04, reltol = 1e-04, derivSwitchTol = 2e-04, resetHessianAndEta = 0L,     stateTrim = Inf, gillK = 10L, gillKcov = 10L, gillRtol = 1.49011611938477e-08,     gillStep = 4, gillStepCov = 2, scaleType = 2L, normType = 1L,     scaleC = NULL, scaleCmin = 1e-05, scaleCmax = 1e+05, scaleC0 = 1e+05,     outerOptTxt = "nlminb", rmatNorm = 1L, smatNorm = 1L, covGillF = 1L,     optGillF = 1L, gillFtol = 0, gillFtolCov = 0, covSmall = 1e-05,     adjLik = TRUE, gradTrim = Inf, gradCalcCentralSmall = 1e-04,     gradCalcCentralLarge = 10000, etaNudge = 1.13158573407617,     etaNudge2 = 1.51818157425799, maxOdeRecalc = 5L, odeRecalcFactor = 3.16227766016838,     nRetries = 3, seed = 42, resetThetaCheckPer = 0.1, etaMat = NULL,     repeatGillMax = 3L, stickyRecalcN = 5L, eventFD = 1.49011611938477e-08,     eventType = 1L, gradProgressOfvTime = 10, addProp = "combined2",     badSolveObjfAdj = 100, compress = TRUE, rxControl = list(        scale = NULL, method = c(liblsoda = 2L), atol = c(5e-06,         5e-06, 1.58113883008419e-05, 1.58113883008419e-05, 1.58113883008419e-05,         1.58113883008419e-05, 1.58113883008419e-05, 1.58113883008419e-05        ), rtol = c(5e-06, 5e-06, 1.58113883008419e-05, 1.58113883008419e-05,         1.58113883008419e-05, 1.58113883008419e-05, 1.58113883008419e-05,         1.58113883008419e-05), maxsteps = 500000L, hmin = 0,         hmax = NA_real_, hini = 0, maxordn = 12L, maxords = 5L,         covsInterpolation = c(locf = 1L), addCov = TRUE, returnType = c(rxSolve = 0L),         sigma = NULL, sigmaDf = NULL, nCoresRV = 1L, sigmaIsChol = FALSE,         sigmaSeparation = "auto", sigmaXform = c(identity = 4L),         nDisplayProgress = 10000L, amountUnits = NA_character_,         timeUnits = "hours", addDosing = FALSE, stateTrim = Inf,         updateObject = FALSE, omega = NULL, omegaDf = NULL, omegaIsChol = FALSE,         omegaSeparation = "auto", omegaXform = c(variance = 6L),         nSub = 1L, thetaMat = NULL, thetaDf = NULL, thetaIsChol = FALSE,         nStud = 1L, dfSub = 0, dfObs = 0, seed = NULL, nsim = NULL,         minSS = 10L, maxSS = 1000L, strictSS = 1L, infSSstep = 12,         istateReset = TRUE, subsetNonmem = TRUE, hmaxSd = 0,         maxAtolRtolFactor = 0.1, from = NULL, to = NULL, by = NULL,         length.out = NULL, iCov = NULL, keep = NULL, keepF = character(0),         drop = NULL, warnDrop = TRUE, omegaLower = -Inf, omegaUpper = Inf,         sigmaLower = -Inf, sigmaUpper = Inf, thetaLower = -Inf,         thetaUpper = Inf, indLinPhiM = 0L, indLinPhiTol = 1e-07,         indLinMatExpType = c(expokit = 2L), indLinMatExpOrder = 6L,         idFactor = TRUE, mxhnil = 0L, hmxi = 0, warnIdSort = TRUE,         ssAtol = c(5e-04, 5e-04, 0.00210848251714291, 0.00210848251714291,         0.00210848251714291, 0.00210848251714291, 0.00210848251714291,         0.00210848251714291), ssRtol = c(5e-04, 5e-04, 0.00210848251714291,         0.00210848251714291, 0.00210848251714291, 0.00210848251714291,         0.00210848251714291, 0.00210848251714291), safeZero = 1L,         sumType = c(pairwise = 1L), prodType = c(`long double` = 1L),         sensType = c(advan = 4L), linDiff = c(tlag = 1.5e-05,         f = 1.5e-05, rate = 1.5e-05, dur = 1.5e-05, tlag2 = 1.5e-05,         f2 = 1.5e-05, rate2 = 1.5e-05, dur2 = 1.5e-05), linDiffCentral = c(tlag = TRUE,         f = TRUE, rate = TRUE, dur = TRUE, tlag2 = TRUE, f2 = TRUE,         rate2 = TRUE, dur2 = TRUE), resample = NULL, resampleID = TRUE,         maxwhile = 100000L, cores = 1L, atolSens = 1.58113883008419e-05,         rtolSens = 1.58113883008419e-05, ssAtolSens = 0.00210848251714291,         ssRtolSens = 0.00210848251714291, simVariability = NA,         nLlikAlloc = NULL, useStdPow = 0L), genRxControl = TRUE,     skipCov = NULL, fallbackFD = FALSE, foceiMuRef = c(0L, 0L,     0L), predNeq = 2L, nfixed = 0L, nomega = 3L, neta = 3L, ntheta = 4L,     nF = 0, printTop = TRUE)), <environment>)
   6: doTryCatch(return(expr), name, parentenv, handler)
   7: tryCatchOne(expr, names, parentenv, handlers[[1L]])
   8: tryCatchList(expr, names[-nh], parentenv, handlers[-nh])
   9: doTryCatch(return(expr), name, parentenv, handler)
  10: tryCatchOne(tryCatchList(expr, names[-nh], parentenv, handlers[-nh]),     names[nh], parentenv, handlers[[nh]])
  11: tryCatchList(expr, classes, parentenv, handlers)
  12: tryCatch(evalq((function (par, fn, gr, lower = -Inf, upper = Inf,     control = list(), ...) {    .ctl <- control    .ctl <- .ctl[names(.ctl) %in% c("eval.max", "iter.max", "trace",         "abs.tol", "rel.tol", "x.tol", "xf.tol", "step.min",         "step.max", "sing.tol", "scale.inti", "diff.g")]    .ctl$trace <- 0    .ret <- stats::nlminb(start = par, objective = fn, gradient = gr,         hessian = NULL, control = .ctl, lower = lower, upper = upper)    .ret$x <- .ret$par    return(.ret)})(par = c(-1, -0.633333333333333, 1, -0.833333333333333, -0.542520422355001, -0.39919989679531, -0.114480393307385), fn = function (theta) {    .Call(`_nlmixr2est_foceiOuterF`, theta)}, gr = function (theta) {    .Call(`_nlmixr2est_foceiOuterG`, theta)}, lower = c(-Inf, -Inf, -Inf, -2.83333163034348, -0.873779194190821, -0.730458752094879, -0.44573935454913), upper = c(Inf, Inf, Inf, Inf, 1.61975587753649, 1.76307631963243, 2.04779571717818), control = list(    maxOuterIterations = 5000L, maxInnerIterations = 1000L, n1qn1nsim = 10001L,     print = 0L, lbfgsLmm = 7L, lbfgsPgtol = 0, lbfgsFactr = 450359962737.05,     scaleTo = 1, epsilon = 1e-04, derivEps = c(2.98023223876953e-07,     2.98023223876953e-07), derivMethod = 3L, covDerivMethod = 1L,     covMethod = 1L, centralDerivEps = c(2.98023223876953e-07,     2.98023223876953e-07), eigen = 1L, addPosthoc = 1L, diagXform = "sqrt",     sumProd = FALSE, optExpression = TRUE, outerOpt = -1L, ci = 0.95,     sigdig = 3, sigdigTable = 3, scaleObjective = 0, useColor = FALSE,     boundTol = 0.05, calcTables = TRUE, printNcol = 4L, noAbort = 1L,     interaction = 1L, cholSEtol = 6.05545445239334e-06, hessEps = 6.05545445239334e-06,     cholAccept = 0.001, resetEtaSize = 1.43953147093846, resetThetaSize = 1.95996398454005,     resetThetaFinalSize = 1.43953147093846, diagOmegaBoundUpper = 5,     diagOmegaBoundLower = 100, cholSEOpt = 0L, cholSECov = 0L,     fo = 0L, covTryHarder = 0L, outerOptFun = function (par,         fn, gr, lower = -Inf, upper = Inf, control = list(),         ...)     {        .ctl <- control        .ctl <- .ctl[names(.ctl) %in% c("eval.max", "iter.max",             "trace", "abs.tol", "rel.tol", "x.tol", "xf.tol",             "step.min", "step.max", "sing.tol", "scale.inti",             "diff.g")]        .ctl$trace <- 0        .ret <- stats::nlminb(start = par, objective = fn, gradient = gr,             hessian = NULL, control = .ctl, lower = lower, upper = upper)        .ret$x <- .ret$par        return(.ret)    }, rhobeg = 0.2, rhoend = 1e-04, npt = NULL, rel.tol = 1e-04,     x.tol = 1e-04, eval.max = 4000, iter.max = 2000, innerOpt = 1L,     abstol = 1e-04, reltol = 1e-04, derivSwitchTol = 2e-04, resetHessianAndEta = 0L,     stateTrim = Inf, gillK = 10L, gillKcov = 10L, gillRtol = 1.49011611938477e-08,     gillStep = 4, gillStepCov = 2, scaleType = 2L, normType = 1L,     scaleC = NULL, scaleCmin = 1e-05, scaleCmax = 1e+05, scaleC0 = 1e+05,     outerOptTxt = "nlminb", rmatNorm = 1L, smatNorm = 1L, covGillF = 1L,     optGillF = 1L, gillFtol = 0, gillFtolCov = 0, covSmall = 1e-05,     adjLik = TRUE, gradTrim = Inf, gradCalcCentralSmall = 1e-04,     gradCalcCentralLarge = 10000, etaNudge = 1.13158573407617,     etaNudge2 = 1.51818157425799, maxOdeRecalc = 5L, odeRecalcFactor = 3.16227766016838,     nRetries = 3, seed = 42, resetThetaCheckPer = 0.1, etaMat = NULL,     repeatGillMax = 3L, stickyRecalcN = 5L, eventFD = 1.49011611938477e-08,     eventType = 1L, gradProgressOfvTime = 10, addProp = "combined2",     badSolveObjfAdj = 100, compress = TRUE, rxControl = list(        scale = NULL, method = c(liblsoda = 2L), atol = c(5e-06,         5e-06, 1.58113883008419e-05, 1.58113883008419e-05, 1.58113883008419e-05,         1.58113883008419e-05, 1.58113883008419e-05, 1.58113883008419e-05        ), rtol = c(5e-06, 5e-06, 1.58113883008419e-05, 1.58113883008419e-05,         1.58113883008419e-05, 1.58113883008419e-05, 1.58113883008419e-05,         1.58113883008419e-05), maxsteps = 500000L, hmin = 0,         hmax = NA_real_, hini = 0, maxordn = 12L, maxords = 5L,         covsInterpolation = c(locf = 1L), addCov = TRUE, returnType = c(rxSolve = 0L),         sigma = NULL, sigmaDf = NULL, nCoresRV = 1L, sigmaIsChol = FALSE,         sigmaSeparation = "auto", sigmaXform = c(identity = 4L),         nDisplayProgress = 10000L, amountUnits = NA_character_,         timeUnits = "hours", addDosing = FALSE, stateTrim = Inf,         updateObject = FALSE, omega = NULL, omegaDf = NULL, omegaIsChol = FALSE,         omegaSeparation = "auto", omegaXform = c(variance = 6L),         nSub = 1L, thetaMat = NULL, thetaDf = NULL, thetaIsChol = FALSE,         nStud = 1L, dfSub = 0, dfObs = 0, seed = NULL, nsim = NULL,         minSS = 10L, maxSS = 1000L, strictSS = 1L, infSSstep = 12,         istateReset = TRUE, subsetNonmem = TRUE, hmaxSd = 0,         maxAtolRtolFactor = 0.1, from = NULL, to = NULL, by = NULL,         length.out = NULL, iCov = NULL, keep = NULL, keepF = character(0),         drop = NULL, warnDrop = TRUE, omegaLower = -Inf, omegaUpper = Inf,         sigmaLower = -Inf, sigmaUpper = Inf, thetaLower = -Inf,         thetaUpper = Inf, indLinPhiM = 0L, indLinPhiTol = 1e-07,         indLinMatExpType = c(expokit = 2L), indLinMatExpOrder = 6L,         idFactor = TRUE, mxhnil = 0L, hmxi = 0, warnIdSort = TRUE,         ssAtol = c(5e-04, 5e-04, 0.00210848251714291, 0.00210848251714291,         0.00210848251714291, 0.00210848251714291, 0.00210848251714291,         0.00210848251714291), ssRtol = c(5e-04, 5e-04, 0.00210848251714291,         0.00210848251714291, 0.00210848251714291, 0.00210848251714291,         0.00210848251714291, 0.00210848251714291), safeZero = 1L,         sumType = c(pairwise = 1L), prodType = c(`long double` = 1L),         sensType = c(advan = 4L), linDiff = c(tlag = 1.5e-05,         f = 1.5e-05, rate = 1.5e-05, dur = 1.5e-05, tlag2 = 1.5e-05,         f2 = 1.5e-05, rate2 = 1.5e-05, dur2 = 1.5e-05), linDiffCentral = c(tlag = TRUE,         f = TRUE, rate = TRUE, dur = TRUE, tlag2 = TRUE, f2 = TRUE,         rate2 = TRUE, dur2 = TRUE), resample = NULL, resampleID = TRUE,         maxwhile = 100000L, cores = 1L, atolSens = 1.58113883008419e-05,         rtolSens = 1.58113883008419e-05, ssAtolSens = 0.00210848251714291,         ssRtolSens = 0.00210848251714291, simVariability = NA,         nLlikAlloc = NULL, useStdPow = 0L), genRxControl = TRUE,     skipCov = NULL, fallbackFD = FALSE, foceiMuRef = c(0L, 0L,     0L), predNeq = 2L, nfixed = 0L, nomega = 3L, neta = 3L, ntheta = 4L,     nF = 0, printTop = TRUE)), <environment>), error = function (x) x, interrupt = function (x) x)
  13: foceiFitCpp_(.ret)
  14: doTryCatch(return(expr), name, parentenv, handler)
  15: tryCatchOne(expr, names, parentenv, handlers[[1L]])
  16: tryCatchList(expr, classes, parentenv, handlers)
  17: tryCatch({    foceiFitCpp_(.ret)}, error = function(e) {    if (regexpr("theta reset", e$message) != -1) {        assign("zeroOuter", FALSE, this.env)        assign("zeroGrad", FALSE, this.env)        if (regexpr("theta reset0", e$message) != -1) {            assign("zeroGrad", TRUE, this.env)        }        else if (regexpr("theta resetZ", e$message) != -1) {            assign("zeroOuter", TRUE, this.env)        }        assign("err", "theta reset", this.env)    }    else {        assign("err", e$message, this.env)    }})
  18: .foceiFitInternal(.env)
  19: doTryCatch(return(expr), name, parentenv, handler)
  20: tryCatchOne(expr, names, parentenv, handlers[[1L]])
  21: tryCatchList(expr, classes, parentenv, handlers)
  22: tryCatch(expr, error = function(e) {    call <- conditionCall(e)    if (!is.null(call)) {        if (identical(call[[1L]], quote(doTryCatch)))             call <- sys.call(-4L)        dcall <- deparse(call, nlines = 1L)        prefix <- paste("Error in", dcall, ": ")        LONG <- 75L        sm <- strsplit(conditionMessage(e), "\n")[[1L]]        w <- 14L + nchar(dcall, type = "w") + nchar(sm[1L], type = "w")        if (is.na(w))             w <- 14L + nchar(dcall, type = "b") + nchar(sm[1L],                 type = "b")        if (w > LONG)             prefix <- paste0(prefix, "\n  ")    }    else prefix <- "Error : "    msg <- paste0(prefix, conditionMessage(e), "\n")    .Internal(seterrmessage(msg[1L]))    if (!silent && isTRUE(getOption("show.error.messages"))) {        cat(msg, file = outFile)        .Internal(printDeferredWarnings())    }    invisible(structure(msg, class = "try-error", condition = e))})
  23: try(.foceiFitInternal(.env))
  24: .foceiFamilyReturn(env, .ui, ..., est = "focei")
  25: nlmixr2Est.focei(env, ...)
  26: nlmixr2Est(env, ...)
  27: withCallingHandlers(expr, warning = function(w) {    assign("ws", unique(c(w$message, ws)), this.env)})
  28: withCallingHandlers(expr, warning = function(w) if (inherits(w,     classes)) tryInvokeRestart("muffleWarning"))
  29: suppressWarnings(withCallingHandlers(expr, warning = function(w) {    assign("ws", unique(c(w$message, ws)), this.env)}))
  30: .collectWarnings(nlmixr2Est(env, ...), lst = TRUE)
  31: doTryCatch(return(expr), name, parentenv, handler)
  32: tryCatchOne(expr, names, parentenv, handlers[[1L]])
  33: tryCatchList(expr, classes, parentenv, handlers)
  34: tryCatch(expr, error = function(e) {    call <- conditionCall(e)    if (!is.null(call)) {        if (identical(call[[1L]], quote(doTryCatch)))             call <- sys.call(-4L)        dcall <- deparse(call, nlines = 1L)        prefix <- paste("Error in", dcall, ": ")        LONG <- 75L        sm <- strsplit(conditionMessage(e), "\n")[[1L]]        w <- 14L + nchar(dcall, type = "w") + nchar(sm[1L], type = "w")        if (is.na(w))             w <- 14L + nchar(dcall, type = "b") + nchar(sm[1L],                 type = "b")        if (w > LONG)             prefix <- paste0(prefix, "\n  ")    }    else prefix <- "Error : "    msg <- paste0(prefix, conditionMessage(e), "\n")    .Internal(seterrmessage(msg[1L]))    if (!silent && isTRUE(getOption("show.error.messages"))) {        cat(msg, file = outFile)        .Internal(printDeferredWarnings())    }    invisible(structure(msg, class = "try-error", condition = e))})
  35: try(.collectWarnings(nlmixr2Est(env, ...), lst = TRUE))
  36: assign("ret", try(.collectWarnings(nlmixr2Est(env, ...), lst = TRUE)),     envir = .envReset)
  37: nlmixr2Est0(.env)
  38: nlmixr2.function(one.compartment, nlmixr2data::theo_sd, est = "focei",     control = list(print = 0))
  39: nlmixr(one.compartment, nlmixr2data::theo_sd, est = "focei",     control = list(print = 0))
  40: withCallingHandlers(expr, warning = function(w) if (inherits(w,     classes)) tryInvokeRestart("muffleWarning"))
  41: suppressWarnings(nlmixr(one.compartment, nlmixr2data::theo_sd,     est = "focei", control = list(print = 0)))
  42: withCallingHandlers(expr, message = function(c) if (inherits(c,     classes)) tryInvokeRestart("muffleMessage"))
  43: suppressMessages(suppressWarnings(nlmixr(one.compartment, nlmixr2data::theo_sd,     est = "focei", control = list(print = 0))))
  44: eval(code, test_env)
  45: eval(code, test_env)
  46: withCallingHandlers({    eval(code, test_env)    if (!handled && !is.null(test)) {        skip_empty()    }}, expectation = handle_expectation, skip = handle_skip, warning = handle_warning,     message = handle_message, error = handle_error)
  47: doTryCatch(return(expr), name, parentenv, handler)
  48: tryCatchOne(expr, names, parentenv, handlers[[1L]])
  49: tryCatchList(expr, names[-nh], parentenv, handlers[-nh])
  50: doTryCatch(return(expr), name, parentenv, handler)
  51: tryCatchOne(tryCatchList(expr, names[-nh], parentenv, handlers[-nh]),     names[nh], parentenv, handlers[[nh]])
  52: tryCatchList(expr, classes, parentenv, handlers)
  53: tryCatch(withCallingHandlers({    eval(code, test_env)    if (!handled && !is.null(test)) {        skip_empty()    }}, expectation = handle_expectation, skip = handle_skip, warning = handle_warning,     message = handle_message, error = handle_error), error = handle_fatal,     skip = function(e) {    })
  54: test_code(desc, code, env = parent.frame(), reporter = reporter)
  55: test_that("precondition tests", {    one.compartment <- function() {        ini({            tka <- 0.45            label("Log Ka")            tcl <- 1            label("Log Cl")            tv <- 3.45            label("Log V")            eta.ka ~ 0.6            eta.cl ~ 0.3            eta.v ~ 0.1            add.sd <- 0.7        })        model({            ka <- exp(tka + eta.ka)            cl <- exp(tcl + eta.cl)            v <- exp(tv + eta.v)            d/dt(depot) <- -ka * depot            d/dt(center) <- ka * depot - cl/v * center            cp <- center/v            cp ~ add(add.sd)        })    }    fit2 <- suppressMessages(suppressWarnings(nlmixr(one.compartment,         nlmixr2data::theo_sd, est = "focei", control = list(print = 0))))    df1 <- fit2$parFixedDf    cov1 <- fit2$cov    suppressWarnings(preconditionFit(fit2, estType = "none"))    df2 <- fit2$parFixedDf    cov2 <- fit2$cov    expect_equal(df1$Estimate, df2$Estimate)    expect_equal(df1$`Back-transformed`, df2$`Back-transformed`)    expect_equal(df1$`BSV(CV%)`, df2$`BSV(CV%)`)    expect_equal(df1$`Shrink(SD)%`, df2$`Shrink(SD)%`)    expect_false(isTRUE(all.equal(df1$SE, df2$SE)))    expect_false(isTRUE(all.equal(df1$`%RSE`, df2$`%RSE`)))    expect_false(isTRUE(all.equal(df1$`CI Lower`, df2$`CI Lower`)))    expect_false(isTRUE(all.equal(df1$`%RSE`, df2$`%RSE`)))    expect_false(isTRUE(all.equal(cov1, cov2)))    skip_if_not(any(names(fit2$covList) == "r,s"))    setCov(fit2, "r,s")    df3 <- fit2$parFixedDf    cov3 <- fit2$cov    expect_equal(df1$Estimate, df3$Estimate)    expect_equal(df1$`Back-transformed`, df3$`Back-transformed`)    expect_equal(df1$`BSV(CV%)`, df3$`BSV(CV%)`)    expect_equal(df1$`Shrink(SD)%`, df3$`Shrink(SD)%`)    expect_equal(df1$SE, df3$SE)    expect_equal(df1$`%RSE`, df3$`%RSE`)    expect_equal(df1$`CI Lower`, df3$`CI Lower`)    expect_equal(df1$`%RSE`, df3$`%RSE`)    expect_equal(cov1, cov3)    setCov(fit2, "precondition")    df4 <- fit2$parFixedDf    cov4 <- fit2$cov    expect_equal(df2$Estimate, df4$Estimate)    expect_equal(df2$`Back-transformed`, df4$`Back-transformed`)    expect_equal(df2$`BSV(CV%)`, df4$`BSV(CV%)`)    expect_equal(df2$`Shrink(SD)%`, df4$`Shrink(SD)%`)    expect_equal(df2$SE, df4$SE)    expect_equal(df2$`%RSE`, df4$`%RSE`)    expect_equal(df2$`CI Lower`, df4$`CI Lower`)    expect_equal(df2$`%RSE`, df4$`%RSE`)    expect_equal(cov2, cov4)})
  56: eval(code, test_env)
  57: eval(code, test_env)
  58: withCallingHandlers({    eval(code, test_env)    if (!handled && !is.null(test)) {        skip_empty()    }}, expectation = handle_expectation, skip = handle_skip, warning = handle_warning,     message = handle_message, error = handle_error)
  59: doTryCatch(return(expr), name, parentenv, handler)
  60: tryCatchOne(expr, names, parentenv, handlers[[1L]])
  61: tryCatchList(expr, names[-nh], parentenv, handlers[-nh])
  62: doTryCatch(return(expr), name, parentenv, handler)
  63: tryCatchOne(tryCatchList(expr, names[-nh], parentenv, handlers[-nh]),     names[nh], parentenv, handlers[[nh]])
  64: tryCatchList(expr, classes, parentenv, handlers)
  65: tryCatch(withCallingHandlers({    eval(code, test_env)    if (!handled && !is.null(test)) {        skip_empty()    }}, expectation = handle_expectation, skip = handle_skip, warning = handle_warning,     message = handle_message, error = handle_error), error = handle_fatal,     skip = function(e) {    })
  66: test_code(NULL, exprs, env)
  67: source_file(path, child_env(env), wrap = wrap)
  68: FUN(X[[i]], ...)
  69: lapply(test_paths, test_one_file, env = env, wrap = wrap)
  70: doTryCatch(return(expr), name, parentenv, handler)
  71: tryCatchOne(expr, names, parentenv, handlers[[1L]])
  72: tryCatchList(expr, classes, parentenv, handlers)
  73: tryCatch(code, testthat_abort_reporter = function(cnd) {    cat(conditionMessage(cnd), "\n")    NULL})
  74: with_reporter(reporters$multi, lapply(test_paths, test_one_file,     env = env, wrap = wrap))
  75: test_files(test_dir = test_dir, test_package = test_package,     test_paths = test_paths, load_helpers = load_helpers, reporter = reporter,     env = env, stop_on_failure = stop_on_failure, stop_on_warning = stop_on_warning,     wrap = wrap, load_package = load_package)
  76: test_files(test_dir = path, test_paths = test_paths, test_package = package,     reporter = reporter, load_helpers = load_helpers, env = env,     stop_on_failure = stop_on_failure, stop_on_warning = stop_on_warning,     wrap = wrap, load_package = load_package, parallel = parallel)
  77: test_dir("testthat", package = package, reporter = reporter,     ..., load_package = "installed")
  78: test_check("nlmixr2extra")
  An irrecoverable exception occurred. R is aborting now ...