inst/models/values-1.1.1.3-U023_solve_saem-unix.R

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

expected_values[[runno]] <- list(lik = c(-11775.8, 23565.59, 23605.7), param = c(1.3824, 
4.1892, -0.014878, 0.19842), stdev_param = c(0.25518, 0.2731, 
0.32361, NA), sigma = c(prop.err = 0.19842), parFixedDf = structure(list(
    Estimate = c(lCl = 1.38237929631301, lVc = 4.18915335054374, 
    lKA = -0.0148782740103172, prop.err = 0.198424894024386), 
    SE = c(lCl = 0.0238332914240093, lVc = 0.0259198898381714, 
    lKA = 0.0334408761988581, prop.err = NA), "%RSE" = c(1.72407757317951, 
    0.618738147525849, 224.763142389156, NA), "Back-transformed" = c(3.98437035627045, 
    65.9669164567393, 0.985231860627464, 0.198424894024386), 
    "CI Lower" = c(3.80253102220525, 62.6993637448713, 0.922727623676538, 
    NA), "CI Upper" = c(4.17490535730593, 69.4047563946194, 1.05197004434293, 
    NA), "BSV(CV%)" = c(25.9386724040219, 27.8271441173093, 33.2271256328621, 
    NA), "Shrink(SD)%" = c(1.42965004916147, 2.5625343136899, 
    10.2898688039981, NA)), class = "data.frame", row.names = c("lCl", 
"lVc", "lKA", "prop.err")), omega = structure(c(0.0651147356643871, 
0, 0, 0, 0.0745832116840361, 0, 0, 0, 0.104724082180979), .Dim = c(3L, 
3L), .Dimnames = list(c("eta.Cl", "eta.Vc", "eta.KA"), c("eta.Cl", 
"eta.Vc", "eta.KA"))), time = structure(list(saem = 22.438, setup = 10.651845, 
    table = 0.0760000000000218, cwres = 10.742, covariance = 0.0440000000000396, 
    other = 0.205154999999948), class = "data.frame", row.names = "elapsed"), 
    objDf = structure(list(OBJF = 19374.1002527917, AIC = 23565.5948247402, 
        BIC = 23605.6968155071, "Log-likelihood" = -11775.7974123701, 
        "Condition Number" = 2.02309869179318), row.names = "FOCEi", class = "data.frame"))