expected_values[[runno]] <- list(lik = c(-13469.81, 26957.61, 27009.2), param = c(1.359,
4.1851, 1.4021, 3.952, 0.19608), stdev_param = c(0.34246, 0.31681,
0.3188, 0.43505, NA), sigma = c(prop.err = 0.19608), parFixedDf = structure(list(
Estimate = c(lCl = 1.35900168716919, lVc = 4.18507497363312,
lQ = 1.40213518747286, lVp = 3.95199440311207, prop.err = 0.196084292172077
), SE = c(lCl = 0.0293777339469019, lVc = 0.0340474087118511,
lQ = 0.0813863709996205, lVp = 0.043369865865096, prop.err = NA
), "%RSE" = c(2.16171431016366, 0.813543578701869, 5.80445963604318,
1.09741718841868, NA), "Back-transformed" = c(3.89230562291345,
65.6984263818112, 4.06386782947659, 52.0390502509691, 0.196084292172077
), "CI Lower" = c(3.6745195399372, 61.4573401971232, 3.46468192357837,
47.7983455991572, NA), "CI Upper" = c(4.12299972758414, 70.2321840678733,
4.7666776055442, 56.6559933628883, NA), "BSV(CV%)" = c(32.4922876882507,
35.2748734089265, 45.6470242627218, 32.7072954489592, NA),
"Shrink(SD)%" = c(0.684521869413601, 5.9395409111898, 49.6266917932384,
30.5596437166487, NA)), class = "data.frame", row.names = c("lCl",
"lVc", "lQ", "lVp", "prop.err")), omega = structure(c(0.117277725254432,
0, 0, 0, 0, 0.100365449389568, 0, 0, 0, 0, 0.101632621489561,
0, 0, 0, 0, 0.189268274386435), .Dim = c(4L, 4L), .Dimnames = list(
c("eta.Vc", "eta.Cl", "eta.Vp", "eta.Q"), c("eta.Vc", "eta.Cl",
"eta.Vp", "eta.Q"))), time = structure(list(saem = 193.761,
setup = 79.790487, table = 0.434000000000083, cwres = 80.339,
covariance = 0.114999999999952, other = 0.364512999999988), class = "data.frame", row.names = "elapsed"),
objDf = structure(list(OBJF = 22749.2546736528, AIC = 26957.6143850661,
BIC = 27009.2017615636, "Log-likelihood" = -13469.8071925331,
"Condition Number" = 8.01919580633504), row.names = "FOCEi", class = "data.frame"))
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