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parameter-estimates

Source: vignettes/ext.Rmd
ext.Rmd
library(ggplot2)
library(dplyr)
#> 
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union
library(tidyr)
library(hyperion)
#> 
#> 
#> ── pharos configuration ────────────────────────────────────────────────────────
#> ✔ pharos.toml found: /data/user-homes/tariq/projects/prism-pkgdocs-build/installed-pkgs/2026-03-02/hyperion_0.3.2/vignettes/pharos.toml
#> ── hyperion options ────────────────────────────────────────────────────────────
#> ✔ hyperion.significant_number_display : 4
#> ── hyperion nonmem object options ──────────────────────────────────────────────
#> ✔ hyperion.nonmem_model.show_included_columns : FALSE
#> ✔ hyperion.nonmem_summary.rse_threshold : 50
#> ✔ hyperion.nonmem_summary.shrinkage_threshold : 30

test_data_dir <- system.file("extdata", package = "hyperion")

get parameter estimates 

get_parameters(file.path(test_data_dir, "models", "onecmt", "run002"))
#>    kind       name random_effect    estimate        sd corr    stderr
#> 1 THETA       TVCL          <NA>  1.24679000        NA   NA 0.1288330
#> 2 THETA        TVV          <NA> 40.84820000        NA   NA 3.0272100
#> 3 THETA       TVKA          <NA>  1.24394000        NA   NA 0.1134100
#> 4 OMEGA OM1 (TVCL)          ETA1  0.13041700 0.3611320   NA 0.0601864
#> 5 OMEGA  OM2 (TVV)          ETA2  0.13633200 0.3692310   NA 0.0397114
#> 6 OMEGA OM3 (TVKA)          ETA3  0.11440800 0.3382430   NA 0.0614429
#> 7 SIGMA SIGMA(1,1)          EPS1  0.03723180 0.1929550   NA 0.0115996
#> 8 SIGMA SIGMA(2,2)          EPS2  0.00660722 0.0812848   NA 0.0279207
#>          rse shrinkage fixed diagonal
#> 1  10.333176        NA FALSE       NA
#> 2   7.410877        NA FALSE       NA
#> 3   9.116999        NA FALSE       NA
#> 4  46.149198   18.0601 FALSE     TRUE
#> 5  29.128451    4.9859 FALSE     TRUE
#> 6  53.705073   27.1894 FALSE     TRUE
#> 7  31.155088   15.4384 FALSE     TRUE
#> 8 422.578634   15.4384 FALSE     TRUE

get_parameters(file.path(test_data_dir, "models", "onecmt", "run002.mod"))
#>    kind       name random_effect    estimate        sd corr    stderr
#> 1 THETA       TVCL          <NA>  1.24679000        NA   NA 0.1288330
#> 2 THETA        TVV          <NA> 40.84820000        NA   NA 3.0272100
#> 3 THETA       TVKA          <NA>  1.24394000        NA   NA 0.1134100
#> 4 OMEGA OM1 (TVCL)          ETA1  0.13041700 0.3611320   NA 0.0601864
#> 5 OMEGA  OM2 (TVV)          ETA2  0.13633200 0.3692310   NA 0.0397114
#> 6 OMEGA OM3 (TVKA)          ETA3  0.11440800 0.3382430   NA 0.0614429
#> 7 SIGMA SIGMA(1,1)          EPS1  0.03723180 0.1929550   NA 0.0115996
#> 8 SIGMA SIGMA(2,2)          EPS2  0.00660722 0.0812848   NA 0.0279207
#>          rse shrinkage fixed diagonal
#> 1  10.333176        NA FALSE       NA
#> 2   7.410877        NA FALSE       NA
#> 3   9.116999        NA FALSE       NA
#> 4  46.149198   18.0601 FALSE     TRUE
#> 5  29.128451    4.9859 FALSE     TRUE
#> 6  53.705073   27.1894 FALSE     TRUE
#> 7  31.155088   15.4384 FALSE     TRUE
#> 8 422.578634   15.4384 FALSE     TRUE

get_parameters(file.path(test_data_dir, "models", "onecmt", "run002", "run002.ext"))
#>    kind       name random_effect    estimate        sd corr    stderr
#> 1 THETA       TVCL          <NA>  1.24679000        NA   NA 0.1288330
#> 2 THETA        TVV          <NA> 40.84820000        NA   NA 3.0272100
#> 3 THETA       TVKA          <NA>  1.24394000        NA   NA 0.1134100
#> 4 OMEGA OM1 (TVCL)          ETA1  0.13041700 0.3611320   NA 0.0601864
#> 5 OMEGA  OM2 (TVV)          ETA2  0.13633200 0.3692310   NA 0.0397114
#> 6 OMEGA OM3 (TVKA)          ETA3  0.11440800 0.3382430   NA 0.0614429
#> 7 SIGMA SIGMA(1,1)          EPS1  0.03723180 0.1929550   NA 0.0115996
#> 8 SIGMA SIGMA(2,2)          EPS2  0.00660722 0.0812848   NA 0.0279207
#>          rse shrinkage fixed diagonal
#> 1  10.333176        NA FALSE       NA
#> 2   7.410877        NA FALSE       NA
#> 3   9.116999        NA FALSE       NA
#> 4  46.149198   18.0601 FALSE     TRUE
#> 5  29.128451    4.9859 FALSE     TRUE
#> 6  53.705073   27.1894 FALSE     TRUE
#> 7  31.155088   15.4384 FALSE     TRUE
#> 8 422.578634   15.4384 FALSE     TRUE

get_parameters(file.path(test_data_dir, "models", "onecmt", "run002_metadata.json"))
#>    kind       name random_effect    estimate        sd corr    stderr
#> 1 THETA       TVCL          <NA>  1.24679000        NA   NA 0.1288330
#> 2 THETA        TVV          <NA> 40.84820000        NA   NA 3.0272100
#> 3 THETA       TVKA          <NA>  1.24394000        NA   NA 0.1134100
#> 4 OMEGA OM1 (TVCL)          ETA1  0.13041700 0.3611320   NA 0.0601864
#> 5 OMEGA  OM2 (TVV)          ETA2  0.13633200 0.3692310   NA 0.0397114
#> 6 OMEGA OM3 (TVKA)          ETA3  0.11440800 0.3382430   NA 0.0614429
#> 7 SIGMA SIGMA(1,1)          EPS1  0.03723180 0.1929550   NA 0.0115996
#> 8 SIGMA SIGMA(2,2)          EPS2  0.00660722 0.0812848   NA 0.0279207
#>          rse shrinkage fixed diagonal
#> 1  10.333176        NA FALSE       NA
#> 2   7.410877        NA FALSE       NA
#> 3   9.116999        NA FALSE       NA
#> 4  46.149198   18.0601 FALSE     TRUE
#> 5  29.128451    4.9859 FALSE     TRUE
#> 6  53.705073   27.1894 FALSE     TRUE
#> 7  31.155088   15.4384 FALSE     TRUE
#> 8 422.578634   15.4384 FALSE     TRUE
get_parameters(
  file.path(test_data_dir, "models", "onecmt", "run002")
) |> 
  mutate(
    `95% CI` = paste0(
      "(",
      round(estimate - 1.96 * stderr, 3)," ,", 
      round(estimate + 1.96 * stderr, 3),
      ")"
    )
  )
#>    kind       name random_effect    estimate        sd corr    stderr
#> 1 THETA       TVCL          <NA>  1.24679000        NA   NA 0.1288330
#> 2 THETA        TVV          <NA> 40.84820000        NA   NA 3.0272100
#> 3 THETA       TVKA          <NA>  1.24394000        NA   NA 0.1134100
#> 4 OMEGA OM1 (TVCL)          ETA1  0.13041700 0.3611320   NA 0.0601864
#> 5 OMEGA  OM2 (TVV)          ETA2  0.13633200 0.3692310   NA 0.0397114
#> 6 OMEGA OM3 (TVKA)          ETA3  0.11440800 0.3382430   NA 0.0614429
#> 7 SIGMA SIGMA(1,1)          EPS1  0.03723180 0.1929550   NA 0.0115996
#> 8 SIGMA SIGMA(2,2)          EPS2  0.00660722 0.0812848   NA 0.0279207
#>          rse shrinkage fixed diagonal           95% CI
#> 1  10.333176        NA FALSE       NA   (0.994 ,1.499)
#> 2   7.410877        NA FALSE       NA (34.915 ,46.782)
#> 3   9.116999        NA FALSE       NA   (1.022 ,1.466)
#> 4  46.149198   18.0601 FALSE     TRUE   (0.012 ,0.248)
#> 5  29.128451    4.9859 FALSE     TRUE   (0.058 ,0.214)
#> 6  53.705073   27.1894 FALSE     TRUE  (-0.006 ,0.235)
#> 7  31.155088   15.4384 FALSE     TRUE    (0.014 ,0.06)
#> 8 422.578634   15.4384 FALSE     TRUE  (-0.048 ,0.061)
untransformed_df <- get_parameters(
  file.path(test_data_dir, "models", "onecmt", "run002")
)

transformed_df <- untransformed_df |> 
  mutate(
    transform = case_when(
      kind == "THETA" ~ "Identity",
      kind == "OMEGA" & diagonal ~ "LogNormal",
      kind == "OMEGA" & !diagonal ~ "Identity",
      name == "SIGMA(1,1)" ~ "Proportional",
      name == "SIGMA(2,2)" ~ "AddErr",
      .default = "Identity"
    ),
    cv = compute_cv(estimate, kind, transform),
    rse = compute_rse(estimate, stderr, kind, transform),
    ci_low = compute_ci(estimate, stderr, 0.95, transform)$lower,
    ci_high = compute_ci(estimate, stderr, 0.95, transform)$upper,
  )
transformed_df
#>    kind       name random_effect    estimate        sd corr    stderr
#> 1 THETA       TVCL          <NA>  1.24679000        NA   NA 0.1288330
#> 2 THETA        TVV          <NA> 40.84820000        NA   NA 3.0272100
#> 3 THETA       TVKA          <NA>  1.24394000        NA   NA 0.1134100
#> 4 OMEGA OM1 (TVCL)          ETA1  0.13041700 0.3611320   NA 0.0601864
#> 5 OMEGA  OM2 (TVV)          ETA2  0.13633200 0.3692310   NA 0.0397114
#> 6 OMEGA OM3 (TVKA)          ETA3  0.11440800 0.3382430   NA 0.0614429
#> 7 SIGMA SIGMA(1,1)          EPS1  0.03723180 0.1929550   NA 0.0115996
#> 8 SIGMA SIGMA(2,2)          EPS2  0.00660722 0.0812848   NA 0.0279207
#>          rse shrinkage fixed diagonal    transform       cv      ci_low
#> 1  10.333176        NA FALSE       NA     Identity       NA  0.99428196
#> 2   7.410877        NA FALSE       NA     Identity       NA 34.91497743
#> 3   9.116999        NA FALSE       NA     Identity       NA  1.02166048
#> 4  46.149198   18.0601 FALSE     TRUE    LogNormal 37.32337  1.01253170
#> 5  29.128451    4.9859 FALSE     TRUE    LogNormal 38.21810  1.06024402
#> 6  53.705073   27.1894 FALSE     TRUE    LogNormal 34.81515  0.99400020
#> 7  31.155088   15.4384 FALSE     TRUE Proportional 19.29554  0.01449700
#> 8 422.578634   15.4384 FALSE     TRUE       AddErr       NA -0.04811635
#>       ci_high
#> 1  1.49929804
#> 2 46.78142257
#> 3  1.46621952
#> 4  1.28194721
#> 5  1.23882694
#> 6  1.26469865
#> 7  0.05996660
#> 8  0.06133079

Read ext file 

read_ext_file(
  file.path(test_data_dir, "ext", "bql.ext"),
  line_prefixes = "-1000000000",
  parameters_only = TRUE
)
#>     iteration method  THETA1  THETA2  THETA3  THETA4  THETA5 THETA6 THETA7
#> 1 -1000000000   FOCE 26.4911 282.616 297.044 58.7497 1.50949   0.75      1
#>   THETA8 THETA9 SIGMA.1.1. OMEGA.1.1. OMEGA.2.1. OMEGA.2.2. OMEGA.3.1.
#> 1      1   0.75 0.00245104   0.100615          0  0.0360015          0
#>   OMEGA.3.2. OMEGA.3.3.
#> 1          0  0.0111728
read_ext_file(file.path(test_data_dir, "ext", "itsimp.ext"), only_method = "its") |> 
  filter(iteration > 0) |> 
  pivot_longer(
    cols = starts_with("THETA"),
    names_to = "parameter",
    values_to = "value"
  ) |>
  ggplot(aes(x = iteration, y = value, color = parameter)) +
  geom_line() +
  geom_point() +
  labs(
    x = "Iteration",
    y = bquote(Theta ~"value"),
    color = "Parameter"
  ) +
  theme_bw()

read_ext_file(file.path(test_data_dir, "ext", "itsimp.ext"), only_method = "its") |> 
  filter(iteration > 0) |> 
  pivot_longer(
    cols = starts_with("OMEGA"),
    names_to = "parameter",
    values_to = "value"
  ) |>
  ggplot(aes(x = iteration, y = value, color = parameter)) +
  geom_line() +
  geom_point() +
  labs(
    x = "Iteration",
    y = bquote(Omega ~"value"),
    color = "Parameter"
  ) +
  theme_bw()

read_ext_file(file.path(test_data_dir, "ext", "itsimp.ext"), only_method = "its") |> 
  filter(iteration > 0) |> 
  pivot_longer(
    cols = starts_with("SIGMA"),
    names_to = "parameter",
    values_to = "value"
  ) |>
  ggplot(aes(x = iteration, y = value, color = parameter)) +
  geom_line() +
  geom_point() +
  labs(
    x = "Iteration",
    y = bquote(Sigma ~"value"),
    color = "Parameter"
  ) +
  theme_bw()


read_ext_file(file.path(test_data_dir, "ext", "example6.txt.ext")) |> 
  filter(iteration == -1000000000)
#>     iteration method ITERATION  THETA1   THETA2   THETA3    THETA4  THETA5
#> 1 -1000000000  Bayes    -1e+09 3.90686 -2.21701 0.552837 -0.183461 2.26824
#>     THETA6  THETA7    THETA8 SIGMA.1.1. SIGMA.2.1. SIGMA.2.2. OMEGA.1.1.
#> 1 0.238698 3.71188 -0.703886 0.00931609          0  0.0223709   0.281875
#>   OMEGA.2.1. OMEGA.2.2. OMEGA.3.1.  OMEGA.3.2. OMEGA.3.3. OMEGA.4.1. OMEGA.4.2.
#> 1 -0.0347915   0.213765  0.0451677 -0.00980444    0.14051   0.030207  0.0548359
#>   OMEGA.4.3. OMEGA.4.4. OMEGA.5.1. OMEGA.5.2.   OMEGA.5.3. OMEGA.5.4.
#> 1 -0.0143056    0.26165  0.0272446  0.0164947 -0.000745322 -0.0322041
#>   OMEGA.5.5. OMEGA.6.1. OMEGA.6.2. OMEGA.6.3. OMEGA.6.4. OMEGA.6.5. OMEGA.6.6.
#> 1   0.206086 -0.0268258 0.00474677  0.0158401  0.0146191 -0.0737751   0.234941
#>   OMEGA.7.1. OMEGA.7.2. OMEGA.7.3. OMEGA.7.4. OMEGA.7.5.   OMEGA.7.6.
#> 1  0.0297134 -0.0475722  0.0318595 -0.0738601  0.0236572 -0.000315573
#>   OMEGA.7.7. OMEGA.8.1. OMEGA.8.2. OMEGA.8.3. OMEGA.8.4. OMEGA.8.5. OMEGA.8.6.
#> 1   0.247069  0.0958203  0.0735577  0.0413009  0.0461165 0.00398651  -0.051391
#>   OMEGA.8.7. OMEGA.8.8.  MCMCOBJ
#> 1  0.0573565   0.237051 -6490.95