inst/models/values-1.1.1.3-U060_solve_saem-unix.R

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

expected_values[[runno]] <- list(lik = c(-11861.51, 23745.02, 23808.08), param = c(1.3553, 
4.1872, 1.5473, 3.8871, -0.10591, 0.1965), stdev_param = c(0.26454, 
0.31857, 0.27836, 0.47034, 0.32714, NA), sigma = c(prop.err = 0.1965), 
    parFixedDf = structure(list(Estimate = c(lCl = 1.35530661564817, 
    lVc = 4.18724965793146, lQ = 1.54726346531091, lVp = 3.88712553473949, 
    lKA = -0.10590672420683, prop.err = 0.196502950393459), SE = c(lCl = 0.0297500484450864, 
    lVc = 0.0328679906753489, lQ = 0.0792669649870477, lVp = 0.0402260586351582, 
    lKA = 0.0432052795297692, prop.err = NA), "%RSE" = c(2.19507881844571, 
    0.784954167065023, 5.12304250466611, 1.03485360263401, 40.7955961751696, 
    NA), "Back-transformed" = c(3.87794981445859, 65.8414551829657, 
    4.69859470612843, 48.7704957504247, 0.899508546536156, 0.196502950393459
    ), "CI Lower" = c(3.65829646433955, 61.7336757332537, 4.02249786360295, 
    45.0730230306515, 0.826473424893258, NA), "CI Upper" = c(4.11079170593529, 
    70.2225676524122, 5.48832913305364, 52.7712830382972, 0.978997752282342, 
    NA), "BSV(CV%)" = c(32.6824574800664, 26.9241289550994, 49.7596459885841, 
    28.384045224108, 33.6093180213949, NA), "Shrink(SD)%" = c(1.46815341554333, 
    11.2923001599596, 39.4199648860467, 32.7223854167677, 16.635721082592, 
    NA)), class = "data.frame", row.names = c("lCl", "lVc", "lQ", 
    "lVp", "lKA", "prop.err")), omega = structure(c(0.0699838608272501, 
    0, 0, 0, 0, 0, 0.101485891410957, 0, 0, 0, 0, 0, 0.0774844248214528, 
    0, 0, 0, 0, 0, 0.221223498705115, 0, 0, 0, 0, 0, 0.107021898005261
    ), .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 = 28.1840000000001, 
        setup = 16.9429350000001, table = 0.115000000000009, 
        cwres = 17.078, covariance = 0.0480000000000018, other = 0.25206499999986), class = "data.frame", row.names = "elapsed"), 
    objDf = structure(list(OBJF = 19532.6647847428, AIC = 23745.0244961561, 
        BIC = 23808.0757340975, "Log-likelihood" = -11861.512248078, 
        "Condition Number" = 10.7997345828714), row.names = "FOCEi", class = "data.frame"))