inst/models/values-1.1.1.3-U055_saem-unix.R

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

expected_values[[runno]] <- list(lik = c(-31640.66, 63303.32, 63374.28), param = c(7.0703, 
6.4153, 4.2929, 0.41431, 3.9704, 0.20151), stdev_param = c(0.29972, 
0.78462, 0.27858, 0.47744, 0.37889, NA), sigma = c(prop.err = 0.20151), 
    parFixedDf = structure(list(Estimate = c(lVM = 7.07031820163957, 
    lKM = 6.41533302089671, lVc = 4.29292168555496, lQ = 0.414310744176003, 
    lVp = 3.97036030747193, prop.err = 0.201507341335811), SE = c(lVM = 0.0921197526376158, 
    lKM = 0.168017701851846, lVc = 0.0298227781750225, lQ = 0.0858163224381039, 
    lVp = 0.0751341208626993, prop.err = NA), "%RSE" = c(1.30290815788537, 
    2.61900202693392, 0.694696534422504, 20.7130333075911, 1.89237537765281, 
    NA), "Back-transformed" = c(1176.5223460322, 611.144250739414, 
    73.1799653100466, 1.51332731147548, 53.0036250017122, 0.201507341335811
    ), "CI Lower" = c(982.172352048419, 439.669969654109, 69.0250936391558, 
    1.27904517548061, 45.7458069690206, NA), "CI Upper" = c(1409.32986743744, 
    849.494668707239, 77.5849338325521, 1.79052280213407, 61.4129348559677, 
    NA), "BSV(CV%)" = c(30.6579278258917, 92.239656613531, 28.4072796638021, 
    50.5988661893502, 39.2907823075734, NA), "Shrink(SD)%" = c(39.9502229884913, 
    34.4632722200618, 8.04380256766001, 47.1894222805468, 41.2404446042736, 
    NA)), class = "data.frame", row.names = c("lVM", "lKM", "lVc", 
    "lQ", "lVp", "prop.err")), omega = structure(c(0.0898323436885704, 
    0, 0, 0, 0, 0, 0.615626312367723, 0, 0, 0, 0, 0, 0.0776065307163663, 
    0, 0, 0, 0, 0, 0.227951594897376, 0, 0, 0, 0, 0, 0.143560421128324
    ), .Dim = c(5L, 5L), .Dimnames = list(c("eta.VM", "eta.KM", 
    "eta.Vc", "eta.Q", "eta.Vp"), c("eta.VM", "eta.KM", "eta.Vc", 
    "eta.Q", "eta.Vp"))), time = structure(list(saem = 69.277, 
        setup = 87.5428520000001, table = 0.267999999999802, 
        cwres = 87.836, covariance = 0.131999999999834, other = 0.31214800000032), class = "data.frame", row.names = "elapsed"), 
    objDf = structure(list(OBJF = 54680.0578603746, AIC = 63303.3225311704, 
        BIC = 63374.2841184484, "Log-likelihood" = -31640.6612655852, 
        "Condition Number" = 45.7947168946986), row.names = "FOCEi", class = "data.frame"))