inst/models/values-1.1.1.3-U063_saem-unix.R

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

expected_values[[runno]] <- list(lik = c(-38506.27, 77034.54, 77109.87), param = c(1.3447, 
4.2151, 1.4274, 3.8718, -0.074555, 0.19879), stdev_param = c(0.25973, 
0.3175, 0.29593, 0.39366, 0.32311, NA), sigma = c(prop.err = 0.19879), 
    parFixedDf = structure(list(Estimate = c(lCl = 1.34472082058016, 
    lVc = 4.21510136761206, lQ = 1.42736893311852, lVp = 3.87176774751744, 
    lKA = -0.074555387110245, prop.err = 0.198792726410034), 
        SE = c(lCl = 0.0291389459164311, lVc = 0.0277642905904831, 
        lQ = 0.0594004847985805, lVp = 0.0350051583438716, lKA = 0.0365842634032456, 
        prop.err = NA), "%RSE" = c(2.16691416318367, 0.658686189703951, 
        4.1615368963371, 0.904113072544619, 49.0699127470808, 
        NA), "Back-transformed" = c(3.83711514747071, 67.7010282146807, 
        4.1677192057448, 48.0272110672843, 0.928156064753007, 
        0.198792726410034), "CI Lower" = c(3.62411288158728, 
        64.1153854661381, 3.70968186492727, 44.8426142341408, 
        0.863933720260995, NA), "CI Upper" = c(4.06263632950105, 
        71.4871974644164, 4.68231077768568, 51.4379690456435, 
        0.997152513363567, NA), "BSV(CV%)" = c(32.5667632911438, 
        26.4172535611018, 40.9417398779837, 30.2523971959572, 
        33.1730913740404, NA), "Shrink(SD)%" = c(0.0766027973506223, 
        7.51201694058929, 33.634483522819, 17.367544192274, 11.8700318618775, 
        NA)), class = "data.frame", row.names = c("lCl", "lVc", 
    "lQ", "lVp", "lKA", "prop.err")), omega = structure(c(0.067459683420978, 
    0, 0, 0, 0, 0, 0.10080361515323, 0, 0, 0, 0, 0, 0.087571910670615, 
    0, 0, 0, 0, 0, 0.154969721255791, 0, 0, 0, 0, 0, 0.104400914605913
    ), .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 = 459.265, 
        setup = 0.221051999999894, table = 0.582000000000335, 
        cwres = 0.884000000000015, covariance = 0.226000000000113, 
        other = 0.437947999999551), class = "data.frame", row.names = "elapsed"), 
    objDf = structure(list(OBJF = 64220.9162349487, AIC = 77034.5406171578, 
        BIC = 77109.8678994444, "Log-likelihood" = -38506.2703085789, 
        "Condition Number" = 6.43339359715968), row.names = "FOCEi", class = "data.frame"))