A wrapper around mrgsolve::mrgsim() for results generated from mapbayest(). Exported for the purpose of utility but might be prone to changes.
Usage
do_mapbayr_sim(
x,
data,
recsort = 3,
output = "df",
...,
eta = NULL,
nrep = NULL,
new_omega = NULL,
new_sigma = NULL
)Arguments
- x
the model object
- data
NMTRAN-like data set
- recsort
record sorting flag. Defaulted to 3. See
mrgsolve::mrgsim().- output
type of object returned. Defaulted to
"df"for a data.frame. Seemrgsolve::mrgsim().- ...
passed to
mrgsolve::mrgsim().- eta
a matrix of individual point estimates of ETA. Most likely obtained with
get_eta().- nrep
number of replicates. If used, the original "ID" in the data will be replaced by unique identifiers.
- new_omega, new_sigma
New "omega" and "sigma" matrices to use instead of those defined in "$OMEGA" and "$SIGMA".
Value
An output from mrgsolve::mrgsim().
Examples
library(mrgsolve)
mod <- exmodel(1, exdata = FALSE)
dat <- exdata(ID = c(1,2))
# Classic framework
set.seed(123)
do_mapbayr_sim(x = mod, data = dat, Request = "DV")
#> ID time DV
#> 1 1 0.0 0.00000
#> 2 1 1.5 137.02297
#> 3 1 4.4 142.99304
#> 4 1 7.1 144.53870
#> 5 1 24.6 67.94558
#> 6 2 0.0 0.00000
#> 7 2 25.9 33.72063
# No random effect
do_mapbayr_sim(x = zero_re(mod), data = dat)
#> ID time DEPOT CENTRAL DV
#> 1 1 0.0 1.000000e+04 0.000 0.00000
#> 2 1 1.5 2.231302e+03 7368.309 105.26156
#> 3 1 4.4 1.227734e+02 8118.003 115.97146
#> 4 1 7.1 8.251050e+00 7060.194 100.85992
#> 5 1 24.6 2.073399e-07 2600.520 37.15028
#> 6 2 0.0 1.000000e+04 0.000 0.00000
#> 7 2 25.9 5.666652e-08 2414.339 34.49056
do_mapbayr_sim(x = mod, data = dat, new_omega = "zero_re")
#> ID time DEPOT CENTRAL DV
#> 1 1 0.0 1.000000e+04 0.000 0.00000
#> 2 1 1.5 2.231302e+03 7368.309 117.10302
#> 3 1 4.4 1.227734e+02 8118.003 129.11558
#> 4 1 7.1 8.251050e+00 7060.194 132.40069
#> 5 1 24.6 2.073399e-07 2600.520 34.77546
#> 6 2 0.0 1.000000e+04 0.000 0.00000
#> 7 2 25.9 5.666652e-08 2414.339 39.71998
# New random effects
## New omega matrix
do_mapbayr_sim(x = mod, data = dat, new_omega = dmat(0.1, 0.03, 0.01), nrep = 10)
#> ID time DEPOT CENTRAL DV
#> 1 1 0.0 1.000000e+04 0.0000 0.000000
#> 2 1 1.5 2.276094e+03 6804.0806 265.331815
#> 3 1 4.4 1.301442e+02 6177.1725 158.728030
#> 4 1 7.1 9.064991e+00 4345.9003 118.077947
#> 5 1 24.6 2.869783e-07 387.2795 13.522088
#> 6 2 0.0 1.000000e+04 0.0000 0.000000
#> 7 2 25.9 2.141098e-06 4648.6116 56.019397
#> 8 3 0.0 1.000000e+04 0.0000 0.000000
#> 9 3 1.5 2.762745e+03 6989.9395 56.135306
#> 10 3 4.4 2.297557e+02 8598.0402 88.600588
#> 11 3 7.1 2.268191e+01 7942.2810 86.034802
#> 12 3 24.6 6.886618e-06 4061.2451 54.117440
#> 13 4 0.0 1.000000e+04 0.0000 0.000000
#> 14 4 25.9 1.036727e-09 2516.7885 52.007899
#> 15 5 0.0 1.000000e+04 0.0000 0.000000
#> 16 5 1.5 2.334198e+03 7358.5978 152.583347
#> 17 5 4.4 1.401319e+02 8474.2596 91.850326
#> 18 5 7.1 1.021374e+01 7637.2710 120.184071
#> 19 5 24.6 4.335280e-07 3518.8557 39.819529
#> 20 6 0.0 1.000000e+04 0.0000 0.000000
#> 21 6 25.9 4.139697e-07 2327.8765 29.319303
#> 22 7 0.0 1.000000e+04 0.0000 0.000000
#> 23 7 1.5 2.633200e+03 6960.7802 83.970767
#> 24 7 4.4 1.995658e+02 7954.2999 93.251168
#> 25 7 7.1 1.806996e+01 6880.5089 112.721108
#> 26 7 24.6 3.132786e-06 2310.0333 21.769806
#> 27 8 0.0 1.000000e+04 0.0000 0.000000
#> 28 8 25.9 7.249688e-09 2072.4060 33.189774
#> 29 9 0.0 1.000000e+04 0.0000 0.000000
#> 30 9 1.5 2.364118e+03 7188.2189 83.245338
#> 31 9 4.4 1.454665e+02 7881.1208 96.827111
#> 32 9 7.1 1.084845e+01 6718.0997 104.792134
#> 33 9 24.6 5.341592e-07 2129.1815 27.472297
#> 34 10 0.0 1.000000e+04 0.0000 0.000000
#> 35 10 25.9 1.283792e-11 1348.5991 20.993151
#> 36 11 0.0 1.000000e+04 0.0000 0.000000
#> 37 11 1.5 2.545595e+03 7023.1075 74.393243
#> 38 11 4.4 1.807099e+02 7882.0683 85.818048
#> 39 11 7.1 1.539582e+01 6751.4651 92.033760
#> 40 11 24.6 1.798545e-06 2152.0885 32.268981
#> 41 12 0.0 1.000000e+04 0.0000 0.000000
#> 42 12 25.9 8.323596e-08 355.2793 7.171505
#> 43 13 0.0 1.000000e+04 0.0000 0.000000
#> 44 13 1.5 2.529678e+03 7045.8704 93.523065
#> 45 13 4.4 1.774154e+02 7916.2657 91.494866
#> 46 13 7.1 1.494544e+01 6800.7034 95.263939
#> 47 13 24.6 1.622716e-06 2216.2989 32.249572
#> 48 14 0.0 1.000000e+04 0.0000 0.000000
#> 49 14 25.9 2.183283e-08 1781.7069 23.221106
#> 50 15 0.0 1.000000e+04 0.0000 0.000000
#> 51 15 1.5 2.670168e+03 6946.0931 79.566594
#> 52 15 4.4 2.078962e+02 8034.3471 103.015232
#> 53 15 7.1 1.930262e+01 7013.0763 84.420295
#> 54 15 24.6 3.937631e-06 2487.4881 34.088192
#> 55 16 0.0 1.000000e+04 0.0000 0.000000
#> 56 16 25.9 1.729749e-09 2035.4942 28.515754
#> 57 17 0.0 1.000000e+04 0.0000 0.000000
#> 58 17 1.5 2.424954e+03 7347.6667 120.304262
#> 59 17 4.4 1.567222e+02 8793.9428 148.691480
#> 60 17 7.1 1.223480e+01 8176.2887 134.198399
#> 61 17 24.6 8.107715e-07 4582.2766 97.827273
#> 62 18 0.0 1.000000e+04 0.0000 0.000000
#> 63 18 25.9 6.518038e-07 3723.3268 15.571808
#> 64 19 0.0 1.000000e+04 0.0000 0.000000
#> 65 19 1.5 2.192477e+03 7436.1270 39.351482
#> 66 19 4.4 1.166119e+02 8248.8953 75.164909
#> 67 19 7.1 7.593219e+00 7257.4767 80.971182
#> 68 19 24.6 1.555237e-07 2899.1595 30.137121
#> 69 20 0.0 1.000000e+04 0.0000 0.000000
#> 70 20 25.9 8.703064e-08 1901.7247 46.053786
## Matrix with "eta" as mean and "new_omega" as variance covariance matrix
etamat <- get_eta(est001, output = "num")[1:2,]
do_mapbayr_sim(
x = mod, data = dat, nrep = 10,
eta = etamat, new_omega = dmat(0.1, 0.03, 0.01)
)
#> ID time DEPOT CENTRAL DV
#> 1 1 0.0 1.000000e+04 0.0000 0.000000
#> 2 1 1.5 1.793532e+03 7568.3219 119.354688
#> 3 1 4.4 6.469637e+01 7351.0008 143.715406
#> 4 1 7.1 2.934649e+00 5889.5959 85.391901
#> 5 1 24.6 6.057618e-09 1322.1415 29.196512
#> 6 2 0.0 1.000000e+04 0.0000 0.000000
#> 7 2 25.9 2.283347e-07 655.7038 10.851148
#> 8 3 0.0 1.000000e+04 0.0000 0.000000
#> 9 3 1.5 2.117685e+03 7570.1252 125.287126
#> 10 3 4.4 1.053238e+02 8515.9439 167.867253
#> 11 3 7.1 6.442831e+00 7667.1534 126.734090
#> 12 3 24.6 8.813556e-08 3596.1156 69.411687
#> 13 4 0.0 1.000000e+04 0.0000 0.000000
#> 14 4 25.9 5.618410e-09 1691.4945 21.886587
#> 15 5 0.0 1.000000e+04 0.0000 0.000000
#> 16 5 1.5 1.748034e+03 7665.7367 134.336723
#> 17 5 4.4 5.999935e+01 7555.2601 128.637467
#> 18 5 7.1 2.598582e+00 6178.8610 99.572911
#> 19 5 24.6 4.425341e-09 1593.7674 44.641610
#> 20 6 0.0 1.000000e+04 0.0000 0.000000
#> 21 6 25.9 2.055474e-07 2704.4301 64.932326
#> 22 7 0.0 1.000000e+04 0.0000 0.000000
#> 23 7 1.5 2.249374e+03 6841.3859 134.008880
#> 24 7 4.4 1.257132e+02 6224.5774 91.550249
#> 25 7 7.1 8.572190e+00 4404.0178 51.186653
#> 26 7 24.6 2.364479e-07 409.4177 7.944375
#> 27 8 0.0 1.000000e+04 0.0000 0.000000
#> 28 8 25.9 2.024873e-08 2194.1030 34.479422
#> 29 9 0.0 1.000000e+04 0.0000 0.000000
#> 30 9 1.5 2.072071e+03 7053.2729 122.907117
#> 31 9 4.4 9.880687e+01 6417.8915 136.313006
#> 32 9 7.1 5.811867e+00 4641.6989 50.699845
#> 33 9 24.6 6.149278e-08 513.3733 8.071178
#> 34 10 0.0 1.000000e+04 0.0000 0.000000
#> 35 10 25.9 1.239101e-08 1863.2347 19.624588
#> 36 11 0.0 1.000000e+04 0.0000 0.000000
#> 37 11 1.5 1.737039e+03 7371.0028 106.951572
#> 38 11 4.4 5.889900e+01 6498.5237 117.447730
#> 39 11 7.1 2.522116e+00 4739.2870 72.210033
#> 40 11 24.6 2.976316e-09 576.3854 10.021807
#> 41 12 0.0 1.000000e+04 0.0000 0.000000
#> 42 12 25.9 2.317578e-06 2106.4043 30.294332
#> 43 13 0.0 1.000000e+04 0.0000 0.000000
#> 44 13 1.5 1.828884e+03 7542.5852 75.605272
#> 45 13 4.4 6.850874e+01 7373.6094 97.710783
#> 46 13 7.1 3.218704e+00 5922.9161 94.232172
#> 47 13 24.6 8.094584e-09 1347.8501 17.929766
#> 48 14 0.0 1.000000e+04 0.0000 0.000000
#> 49 14 25.9 9.487120e-09 547.0377 12.609039
#> 50 15 0.0 1.000000e+04 0.0000 0.000000
#> 51 15 1.5 2.664677e+03 6770.1071 110.580542
#> 52 15 4.4 2.066447e+02 7293.7041 127.620902
#> 53 15 7.1 1.911545e+01 5898.3858 95.141362
#> 54 15 24.6 3.806941e-06 1251.4617 26.109768
#> 55 16 0.0 1.000000e+04 0.0000 0.000000
#> 56 16 25.9 8.145577e-08 1335.9604 12.006268
#> 57 17 0.0 1.000000e+04 0.0000 0.000000
#> 58 17 1.5 1.568652e+03 7597.8521 152.336690
#> 59 17 4.4 4.367283e+01 6756.9768 110.732688
#> 60 17 7.1 1.556536e+00 5077.0225 123.855190
#> 61 17 24.6 6.572014e-10 762.4210 12.581644
#> 62 18 0.0 1.000000e+04 0.0000 0.000000
#> 63 18 25.9 4.878141e-09 1128.0833 23.508400
#> 64 19 0.0 1.000000e+04 0.0000 0.000000
#> 65 19 1.5 1.984133e+03 7521.9678 121.428969
#> 66 19 4.4 8.700439e+01 7826.2201 149.507273
#> 67 19 7.1 4.733351e+00 6589.6346 116.630795
#> 68 19 24.6 3.033610e-08 2013.9499 28.049690
#> 69 20 0.0 1.000000e+04 0.0000 0.000000
#> 70 20 25.9 5.361778e-08 2529.5491 43.210817