inst/models/values-1.1.1.3-U061_saem-unix.R

In nlmixrdevelopment/nlmixr.examples: Nonlinear Mixed Effects Models in Population Pharmacokinetics and Pharmacodynamics

expected_values[[runno]] <- list(lik = c(-27020.25, 54062.49, 54133.45), param = c(1.3292, 
4.2143, 1.4255, 3.808, -0.087243, 0.19775), stdev_param = c(0.2507, 
0.3215, 0.27264, 0.63136, 0.32341, NA), sigma = c(prop.err = 0.19775), 
    parFixedDf = structure(list(Estimate = c(lCl = 1.32921888556986, 
    lVc = 4.21434800047993, lQ = 1.42554095902141, lVp = 3.8079633715171, 
    lKA = -0.0872427043844921, prop.err = 0.197747200745811), 
        SE = c(lCl = 0.0296166436268834, lVc = 0.0325614414299948, 
        lQ = 0.106224321789321, lVp = 0.0437554494358583, lKA = 0.0483727372739011, 
        prop.err = NA), "%RSE" = c(2.22812389655344, 0.772632953573999, 
        7.4515096263695, 1.14905121627853, 55.4461689549592, 
        NA), "Back-transformed" = c(3.77809111319992, 67.6500436926549, 
        4.16010768194634, 45.0585777717211, 0.916454641079318, 
        0.197747200745811), "CI Lower" = c(3.56502594207159, 
        63.4675497672583, 3.37820706303999, 41.3554521512265, 
        0.833558388316875, NA), "CI Upper" = c(4.00389020769532, 
        72.108162807619, 5.12298257698128, 49.0932954471405, 
        1.00759481390587, NA), "BSV(CV%)" = c(32.9987553766178, 
        25.4695376270661, 69.9826775224093, 27.7789144544083, 
        33.2057637794357, NA), "Shrink(SD)%" = c(0.302981180181627, 
        12.1380234275819, 40.5172751499201, 27.9981285145366, 
        23.6887081282171, NA)), class = "data.frame", row.names = c("lCl", 
    "lVc", "lQ", "lVp", "lKA", "prop.err")), omega = structure(c(0.0628524768386782, 
    0, 0, 0, 0, 0, 0.103361125284871, 0, 0, 0, 0, 0, 0.0743342690284337, 
    0, 0, 0, 0, 0, 0.398613365317948, 0, 0, 0, 0, 0, 0.104596271033096
    ), .Dim = c(5L, 5L), .Dimnames = list(c("eta.Vc", "eta.Cl", 
    "eta.Vp", "eta.Q", "eta.KA"), c("eta.Vc", "eta.Cl", "eta.Vp", 
    "eta.Q", "eta.KA"))), time = structure(list(saem = 420.441, 
        setup = 0.214254000000036, table = 0.322999999999865, 
        cwres = 0.605000000000018, covariance = 0.170999999999822, 
        other = 0.379746000000239), class = "data.frame", row.names = "elapsed"), 
    objDf = structure(list(OBJF = 45439.2269693299, AIC = 54062.4916401257, 
        BIC = 54133.4532274037, "Log-likelihood" = -27020.2458200628, 
        "Condition Number" = 20.5334004529033), row.names = "FOCEi", class = "data.frame"))