inst/models/values-1.1.1.3-U061_solve_saem-unix.R

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

expected_values[[runno]] <- list(lik = c(-27021.37, 54064.75, 54135.71), param = c(1.3293, 
4.212, 1.434, 3.8122, -0.089998, 0.19781), stdev_param = c(0.2486, 
0.32096, 0.27437, 0.6335, 0.32723, NA), sigma = c(prop.err = 0.19781), 
    parFixedDf = structure(list(Estimate = c(lCl = 1.32934763519284, 
    lVc = 4.21200614742817, lQ = 1.43402323446794, lVp = 3.81220136424293, 
    lKA = -0.089997567195022, prop.err = 0.197807304512731), 
        SE = c(lCl = 0.0295743549114232, lVc = 0.0329858290329089, 
        lQ = 0.109642088160802, lVp = 0.0444641624219271, lKA = 0.0493421332568158, 
        prop.err = NA), "%RSE" = c(2.22472693586527, 0.783138197769486, 
        7.64576790148605, 1.16636447484083, 54.8260745203177, 
        NA), "Back-transformed" = c(3.7785775723214, 67.4918025924031, 
        4.19554494302388, 45.2499409079275, 0.91393340869027, 
        0.197807304512731), "CI Lower" = c(3.565780502551, 63.2664460571812, 
        3.38423773008288, 41.4734393755751, 0.829687320632386, 
        NA), "CI Upper" = c(4.00407385138705, 71.9993567056841, 
        5.20134776953219, 49.370324308738, 1.00673380772358, 
        NA), "BSV(CV%)" = c(32.9401246776249, 25.249502930821, 
        70.2706650663069, 27.9616938530742, 33.619186807964, 
        NA), "Shrink(SD)%" = c(0.321360294988127, 12.7159360415739, 
        40.8615476406022, 28.2197566497692, 23.3858876144966, 
        NA)), class = "data.frame", row.names = c("lCl", "lVc", 
    "lQ", "lVp", "lKA", "prop.err")), omega = structure(c(0.0618039165987767, 
    0, 0, 0, 0, 0, 0.103012424287705, 0, 0, 0, 0, 0, 0.0752796583236659, 
    0, 0, 0, 0, 0, 0.401320957556656, 0, 0, 0, 0, 0, 0.10708150884573
    ), .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 = 73.8630000000001, 
        setup = 0.315305000000035, table = 0.331000000000017, 
        cwres = 0.721000000000004, covariance = 0.0879999999999654, 
        other = 0.345694999999907), class = "data.frame", row.names = "elapsed"), 
    objDf = structure(list(OBJF = 45441.4811428444, AIC = 54064.7458136402, 
        BIC = 54135.7074009182, "Log-likelihood" = -27021.3729068201, 
        "Condition Number" = 22.1841667662091), row.names = "FOCEi", class = "data.frame"))