inst/models/values-1.1.1.3-U041_saem-unix.R

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

expected_values[[runno]] <- list(lik = c(-29932.99, 59887.99, 59958.95), param = c(7.0741, 
6.0742, 4.2806, 0.68935, 3.9416, 0.20786), stdev_param = c(0.35887, 
0.37443, 0.29221, 0.99335, 0.29383, NA), sigma = c(prop.err = 0.20786), 
    parFixedDf = structure(list(Estimate = c(lVM = 7.07406688610489, 
    lKM = 6.07423613454204, lVc = 4.28056664637805, lQ = 0.689349582654788, 
    lVp = 3.94159216331911, prop.err = 0.207861844165579), SE = c(lVM = 0.0693413237803309, 
    lKM = 0.114192547032371, lVc = 0.0303123383587689, lQ = 0.126424557364044, 
    lVp = 0.0552935238220321, prop.err = NA), "%RSE" = c(0.980218662005208, 
    1.87994909159027, 0.7081384513524, 18.3396872276565, 1.40282204578647, 
    NA), "Back-transformed" = c(1180.9410340329, 434.51746283491, 
    72.2813863909686, 1.99241920770085, 51.5005333187066, 0.207861844165579
    ), "CI Lower" = c(1030.87206582631, 347.381241340271, 68.1121461563763, 
    1.55513444773549, 46.2110454283931, NA), "CI Upper" = c(1352.85625839983, 
    543.510711113922, 76.7058316824362, 2.55266308645906, 57.395475638419, 
    NA), "BSV(CV%)" = c(37.0744999453948, 38.7940030470165, 29.8563270966351, 
    129.710338188089, 30.0287193528849, NA), "Shrink(SD)%" = c(16.7406365018672, 
    50.2848356864103, 8.45130640826847, 35.5130032892691, 49.4189362401547, 
    NA)), class = "data.frame", row.names = c("lVM", "lKM", "lVc", 
    "lQ", "lVp", "prop.err")), omega = structure(c(0.128790545338518, 
    0, 0, 0, 0, 0, 0.140194429049046, 0, 0, 0, 0, 0, 0.0853884185774305, 
    0, 0, 0, 0, 0, 0.986740689722085, 0, 0, 0, 0, 0, 0.0863358475853246
    ), .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 = 239.222000000001, 
        setup = 0.181558000000371, table = 0.300000000000182, 
        cwres = 0.509999999999309, covariance = 0.131999999999607, 
        other = 0.313441999999526), class = "data.frame", row.names = "elapsed"), 
    objDf = structure(list(OBJF = 51264.7238453173, AIC = 59887.9885161131, 
        BIC = 59958.9501033911, "Log-likelihood" = -29932.9942580565, 
        "Condition Number" = 22.2474010970727), row.names = "FOCEi", class = "data.frame"))