inst/models/values-1.1.1.3-U040_saem-unix.R

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

expected_values[[runno]] <- list(lik = c(-12000.11, 24022.21, 24085.27), param = c(6.903, 
5.4996, 4.2487, 1.3756, 3.9081, 0.19282), stdev_param = c(0.33546, 
0.18129, 0.28865, 0.33544, 0.33364, NA), sigma = c(prop.err = 0.19282), 
    parFixedDf = structure(list(Estimate = c(lVM = 6.90304295330316, 
    lKM = 5.49964061470784, lVc = 4.24873177163665, lQ = 1.37559261231193, 
    lVp = 3.90814836591103, prop.err = 0.192824063587475), SE = c(lVM = 0.125055453934573, 
    lKM = 0.181309960731666, lVc = 0.0276171914762886, lQ = 0.056648604629137, 
    lVp = 0.0597905624635993, prop.err = NA), "%RSE" = c(1.81159895397628, 
    3.2967601600509, 0.650010237423159, 4.11812364519237, 1.52989489818566, 
    NA), "Back-transformed" = c(995.29875990787, 244.604009382695, 
    70.0165590293834, 3.95742124470883, 49.8066428606541, 0.192824063587475
    ), "CI Lower" = c(778.943697200373, 171.447932792916, 66.3273990826536, 
    3.54154611506714, 44.2989518662438, NA), "CI Upper" = c(1271.74739976016, 
    348.975461129397, 73.9109117215064, 4.42213157734807, 55.9991053634625, 
    NA), "BSV(CV%)" = c(34.5124721369103, 18.2785177542417, 29.4772628291526, 
    34.5101151882332, 34.3145842792113, NA), "Shrink(SD)%" = c(10.7439211711418, 
    64.5738299297333, 2.62180476860435, 44.6708599551171, 28.6314590954704, 
    NA)), class = "data.frame", row.names = c("lVM", "lKM", "lVc", 
    "lQ", "lVp", "prop.err")), omega = structure(c(0.112534685619181, 
    0, 0, 0, 0, 0, 0.0328644211332545, 0, 0, 0, 0, 0, 0.083321237315424, 
    0, 0, 0, 0, 0, 0.1125201487352, 0, 0, 0, 0, 0, 0.111316903589007
    ), .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 = 101.892000000001, 
        setup = 10.1338040000002, table = 0.0940000000000509, 
        cwres = 10.2449999999999, covariance = 0.0689999999995052, 
        other = 0.300196), class = "data.frame", row.names = "elapsed"), 
    objDf = structure(list(OBJF = 19809.854274222, AIC = 24022.2139856353, 
        BIC = 24085.2652235767, "Log-likelihood" = -12000.1069928176, 
        "Condition Number" = 67.5236429003065), row.names = "FOCEi", class = "data.frame"))