inst/models/values-1.1.1.3-U060_saem-unix.R

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

expected_values[[runno]] <- list(lik = c(-11859.71, 23741.42, 23804.47), param = c(1.3549, 
4.198, 1.5073, 3.8743, -0.093162, 0.19664), stdev_param = c(0.26778, 
0.31866, 0.28654, 0.42776, 0.33296, NA), sigma = c(prop.err = 0.19664), 
    parFixedDf = structure(list(Estimate = c(lCl = 1.35488771164106, 
    lVc = 4.1980451858651, lQ = 1.50732665312458, lVp = 3.87429890300889, 
    lKA = -0.0931619851259525, prop.err = 0.19664056451678), 
        SE = c(lCl = 0.0297807050525957, lVc = 0.032176714225987, 
        lQ = 0.0755345427139845, lVp = 0.0405494787627503, lKA = 0.0423639714247709, 
        prop.err = NA), "%RSE" = c(2.19802016039579, 0.766468982619021, 
        5.0111594960128, 1.0466275261121, 45.4734528976556, NA
        ), "Back-transformed" = c(3.87632566594686, 66.5560989896001, 
        4.51464543406707, 48.1489293853256, 0.911045912456068, 
        0.19664056451678), "CI Lower" = c(3.65654459704808, 62.4883403439015, 
        3.89339555351949, 44.4703815773357, 0.838455438563556, 
        NA), "CI Upper" = c(4.10931694381871, 70.8886536005716, 
        5.23502508675698, 52.1317631808808, 0.98992101002395, 
        NA), "BSV(CV%)" = c(32.6922560373413, 27.2656817944947, 
        44.8092751379282, 29.252718927208, 34.2409857972984, 
        NA), "Shrink(SD)%" = c(1.54430412262695, 10.3820591464772, 
        42.2917096887197, 32.1102513155842, 16.1423936891456, 
        NA)), class = "data.frame", row.names = c("lCl", "lVc", 
    "lQ", "lVp", "lKA", "prop.err")), omega = structure(c(0.0717081394884644, 
    0, 0, 0, 0, 0, 0.101543765558129, 0, 0, 0, 0, 0, 0.0821071811471725, 
    0, 0, 0, 0, 0, 0.182977269965956, 0, 0, 0, 0, 0, 0.110865395717613
    ), .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 = 11.0490000000002, 
        setup = 109.980913, table = 0.0909999999998945, cwres = 110.102, 
        covariance = 0.0739999999998417, other = 0.247087000000221), class = "data.frame", row.names = "elapsed"), 
    objDf = structure(list(OBJF = 19529.056294734, AIC = 23741.4160061473, 
        BIC = 23804.4672440888, "Log-likelihood" = -11859.7080030737, 
        "Condition Number" = 9.61415643860786), row.names = "FOCEi", class = "data.frame"))