inst/models/values-1.1.1.3-U062_saem-unix.R

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

expected_values[[runno]] <- list(lik = c(-13224.33, 26470.66, 26533.71), param = c(1.3594, 
4.2403, 1.3511, 3.8658, -0.071735, 0.19408), stdev_param = c(0.27789, 
0.3067, 0.32214, 0.31721, 0.37408, NA), sigma = c(prop.err = 0.19408), 
    parFixedDf = structure(list(Estimate = c(lCl = 1.35940267038232, 
    lVc = 4.24029064676919, lQ = 1.3510588834742, lVp = 3.86578482574889, 
    lKA = -0.0717353102310761, prop.err = 0.194082120227429), 
        SE = c(lCl = 0.028540632851487, lVc = 0.040019669731324, 
        lQ = 0.117633646256289, lVp = 0.0562562150945952, lKA = 0.0624368126314993, 
        prop.err = NA), "%RSE" = c(2.09949807171264, 0.943795439159723, 
        8.70677419727248, 1.45523399853734, 87.0377676354584, 
        NA), "Back-transformed" = c(3.89386668508756, 69.4280279385659, 
        3.86151225814661, 47.7407258844945, 0.930777230418682, 
        0.194082120227429), "CI Lower" = c(3.68202936438573, 
        64.1903915665443, 3.06639061179393, 42.7566470675837, 
        0.82356795396055, NA), "CI Upper" = c(4.11789159203631, 
        75.0930309942303, 4.86281064860586, 53.30579136329, 1.05194264601919, 
        NA), "BSV(CV%)" = c(31.4057383007802, 28.334560245317, 
        32.5363315873292, 33.0684862216189, 38.7559906901189, 
        NA), "Shrink(SD)%" = c(0.746891743161704, 15.7927892326796, 
        63.265490909871, 33.9904753951679, 28.708157167797, NA
        )), class = "data.frame", row.names = c("lCl", "lVc", 
    "lQ", "lVp", "lKA", "prop.err")), omega = structure(c(0.0772246456760186, 
    0, 0, 0, 0, 0, 0.0940658057298691, 0, 0, 0, 0, 0, 0.103776492043625, 
    0, 0, 0, 0, 0, 0.100624476894699, 0, 0, 0, 0, 0, 0.139938171573932
    ), .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 = 1104.975, 
        setup = 0.210388000000084, table = 0.777000000000044, 
        cwres = 1.29500000000007, covariance = 0.329000000000178, 
        other = 0.759611999999606), class = "data.frame", row.names = "elapsed"), 
    objDf = structure(list(OBJF = 22258.3029144521, AIC = 26470.6626258654, 
        BIC = 26533.7138638069, "Log-likelihood" = -13224.3313129327, 
        "Condition Number" = 21.8573630522655), row.names = "FOCEi", class = "data.frame"))