diff --git a/README.Rmd b/README.Rmd index fd27275..6799bf7 100644 --- a/README.Rmd +++ b/README.Rmd @@ -18,7 +18,7 @@ knitr::opts_chunk$set( [![R-CMD-check](https://github.com/nlmixr2/nlmixr2extra/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/nlmixr2/nlmixr2extra/actions/workflows/R-CMD-check.yaml) [![Codecov test coverage](https://codecov.io/gh/nlmixr2/nlmixr2extra/graph/badge.svg)](https://app.codecov.io/gh/nlmixr2/nlmixr2extra) -[![CRAN version](http://www.r-pkg.org/badges/version/nlmixr2extra)](https://cran.r-project.org/package=nlmixr2extra) +[![CRAN status](https://www.r-pkg.org/badges/version/nlmixr2extra)](https://CRAN.R-project.org/package=nlmixr2extra) [![CRAN total downloads](https://cranlogs.r-pkg.org/badges/grand-total/nlmixr2extra)](https://cran.r-project.org/package=nlmixr2extra) [![CRAN total downloads](https://cranlogs.r-pkg.org/badges/nlmixr2extra)](https://cran.r-project.org/package=nlmixr2extra) [![CodeFactor](https://www.codefactor.io/repository/github/nlmixr2/nlmixr2extra/badge)](https://www.codefactor.io/repository/github/nlmixr2/nlmixr2extra) @@ -51,13 +51,13 @@ library(nlmixr2extra) # The basic model consists of an ini block that has initial estimates one.compartment <- function() { ini({ - tka <- 0.45 # Log Ka - tcl <- 1 # Log Cl - tv <- 3.45 # Log V + tka <- 0.45; label("Absorption rate, Ka") + tcl <- 1; label("Clearance, Cl") + tv <- 3.45; label("Central volumne, V") eta.ka ~ 0.6 eta.cl ~ 0.3 eta.v ~ 0.1 - add.sd <- 0.7 + add.sd <- 0.7; label("Additive residual error") }) # and a model block with the error specification and model specification model({ diff --git a/README.md b/README.md index 5390022..5c52a09 100644 --- a/README.md +++ b/README.md @@ -5,11 +5,11 @@ -[![R-CMD-check](https://github.com/nlmixr2/nlmixr2extra/workflows/R-CMD-check/badge.svg)](https://github.com/nlmixr2/nlmixr2extra/actions) +[![R-CMD-check](https://github.com/nlmixr2/nlmixr2extra/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/nlmixr2/nlmixr2extra/actions/workflows/R-CMD-check.yaml) [![Codecov test -coverage](https://codecov.io/gh/nlmixr2/nlmixr2extra/branch/main/graph/badge.svg)](https://app.codecov.io/gh/nlmixr2/nlmixr2extra?branch=main) +coverage](https://codecov.io/gh/nlmixr2/nlmixr2extra/graph/badge.svg)](https://app.codecov.io/gh/nlmixr2/nlmixr2extra) [![CRAN -version](http://www.r-pkg.org/badges/version/nlmixr2extra)](https://cran.r-project.org/package=nlmixr2extra) +status](https://www.r-pkg.org/badges/version/nlmixr2extra)](https://CRAN.R-project.org/package=nlmixr2extra) [![CRAN total downloads](https://cranlogs.r-pkg.org/badges/grand-total/nlmixr2extra)](https://cran.r-project.org/package=nlmixr2extra) [![CRAN total @@ -48,13 +48,13 @@ library(nlmixr2extra) # The basic model consists of an ini block that has initial estimates one.compartment <- function() { ini({ - tka <- 0.45 # Log Ka - tcl <- 1 # Log Cl - tv <- 3.45 # Log V + tka <- 0.45; label("Absorption rate, Ka") + tcl <- 1; label("Clearance, Cl") + tv <- 3.45; label("Central volumne, V") eta.ka ~ 0.6 eta.cl ~ 0.3 eta.v ~ 0.1 - add.sd <- 0.7 + add.sd <- 0.7; label("Additive residual error") }) # and a model block with the error specification and model specification model({ @@ -71,7 +71,8 @@ one.compartment <- function() { # The fit is performed by the function nlmixr/nlmixr2 specifying the model, data # and estimate (in a real estimate, nBurn and nEm would be much higher.) fit <- nlmixr2(one.compartment, theo_sd, est="saem", saemControl(print=0, nBurn = 10, nEm = 20)) -#> ℹ parameter labels from comments will be replaced by 'label()' +#> ℹ parameter labels from comments are typically ignored in non-interactive mode +#> ℹ Need to run with the source intact to parse comments #> → loading into symengine environment... #> → pruning branches (`if`/`else`) of saem model... #> ✔ done @@ -80,8 +81,16 @@ fit <- nlmixr2(one.compartment, theo_sd, est="saem", saemControl(print=0, nBurn #> → optimizing duplicate expressions in saem model... #> [====|====|====|====|====|====|====|====|====|====] 0:00:00 #> ✔ done -#> rxode2 2.0.11.9000 using 8 threads (see ?getRxThreads) +#> using C compiler: 'gcc.exe (GCC) 13.2.0' +#> ℹ calculate uninformed etas +#> ℹ done +#> rxode2 3.0.2 using 8 threads (see ?getRxThreads) #> no cache: create with `rxCreateCache()` +#> +#> Attaching package: 'rxode2' +#> The following objects are masked from 'package:nlmixr2est': +#> +#> boxCox, yeoJohnson #> Calculating covariance matrix #> → loading into symengine environment... #> → pruning branches (`if`/`else`) of saem model... @@ -91,203 +100,15 @@ fit <- nlmixr2(one.compartment, theo_sd, est="saem", saemControl(print=0, nBurn #> → optimizing duplicate expressions in saem predOnly model 1... #> → finding duplicate expressions in saem predOnly model 2... #> ✔ done +#> using C compiler: 'gcc.exe (GCC) 13.2.0' #> → Calculating residuals/tables #> ✔ done #> → compress origData in nlmixr2 object, save 5952 -#> → compress phiM in nlmixr2 object, save 2832 -#> → compress parHist in nlmixr2 object, save 1968 -#> → compress saem0 in nlmixr2 object, save 24944 +#> → compress phiM in nlmixr2 object, save 3712 +#> → compress parHistData in nlmixr2 object, save 2456 +#> → compress saem0 in nlmixr2 object, save 27920 # In a real bootstrap, nboot would be much higher. fit2 <- suppressMessages(bootstrapFit(fit, nboot = 5)) -#> 001: 0.289754 0.955016 3.449185 0.381052 0.078862 0.016351 1.435990 -#> 002: 0.341570 1.042356 3.475026 0.361999 0.074919 0.015533 0.968865 -#> 003: 0.472750 1.038382 3.506706 0.343899 0.081378 0.014757 0.797063 -#> 004: 0.496706 1.074803 3.510905 0.326704 0.077309 0.014019 0.722518 -#> 005: 0.534589 1.100823 3.486683 0.310369 0.073930 0.013318 0.689762 -#> 006: 0.536212 1.092222 3.496588 0.294850 0.070233 0.012652 0.646975 -#> 007: 0.498232 1.116233 3.490177 0.296055 0.066722 0.012019 0.657194 -#> 008: 0.472135 1.087746 3.486804 0.281253 0.063386 0.011418 0.665569 -#> 009: 0.414591 1.093383 3.475219 0.275684 0.060216 0.011823 0.654913 -#> 010: 0.463636 1.093226 3.468536 0.302019 0.060954 0.010231 0.644346 -#> 011: 0.471632 1.094277 3.473210 0.300665 0.057946 0.010692 0.645369 -#> 012: 0.487830 1.101393 3.474948 0.306205 0.054575 0.011432 0.636770 -#> 013: 0.479627 1.106742 3.473516 0.303806 0.050805 0.012334 0.635296 -#> 014: 0.488082 1.104715 3.475776 0.299002 0.052067 0.012733 0.636187 -#> 015: 0.491629 1.105114 3.478241 0.293828 0.052474 0.013105 0.633431 -#> 016: 0.496946 1.105220 3.481824 0.288786 0.052556 0.013002 0.633009 -#> 017: 0.501182 1.104867 3.484359 0.291721 0.051772 0.013106 0.630237 -#> 018: 0.504760 1.104384 3.485512 0.294660 0.051390 0.012882 0.628937 -#> 019: 0.503525 1.106547 3.485744 0.294525 0.051059 0.012606 0.628119 -#> 020: 0.504792 1.106269 3.487000 0.292017 0.051074 0.012392 0.628590 -#> 021: 0.504680 1.105623 3.488382 0.289388 0.051105 0.012258 0.629262 -#> 022: 0.506024 1.105160 3.490148 0.285219 0.051702 0.012195 0.629037 -#> 023: 0.511997 1.105357 3.491865 0.290051 0.051408 0.012157 0.629789 -#> 024: 0.515887 1.105808 3.492777 0.292475 0.050884 0.012147 0.630087 -#> 025: 0.517210 1.105963 3.492826 0.295889 0.049986 0.012198 0.629288 -#> 026: 0.516025 1.107520 3.492264 0.297170 0.049610 0.012291 0.628565 -#> 027: 0.515202 1.108956 3.491510 0.296660 0.049518 0.012327 0.628714 -#> 028: 0.516875 1.109118 3.491399 0.297858 0.048998 0.012389 0.628230 -#> 029: 0.518964 1.109633 3.491344 0.299585 0.048763 0.012417 0.628187 -#> 030: 0.520491 1.109555 3.491727 0.299411 0.048814 0.012561 0.627538 -#> 001: 0.322787 0.951634 3.447451 0.381052 0.076738 0.016351 1.530345 -#> 002: 0.427636 0.897920 3.465514 0.361999 0.072901 0.015533 1.087413 -#> 003: 0.508253 0.828660 3.472124 0.343899 0.069256 0.014757 0.838074 -#> 004: 0.509892 0.834282 3.468804 0.326704 0.066873 0.014019 0.673776 -#> 005: 0.508392 0.823533 3.444179 0.310369 0.078466 0.013318 0.654094 -#> 006: 0.461647 0.841721 3.438128 0.294850 0.074543 0.012652 0.607374 -#> 007: 0.449577 0.846887 3.427116 0.328131 0.070816 0.012019 0.613524 -#> 008: 0.452729 0.858913 3.420601 0.316657 0.086343 0.011418 0.600919 -#> 009: 0.423963 0.842949 3.420380 0.329854 0.089491 0.010848 0.594947 -#> 010: 0.428721 0.855938 3.425315 0.354540 0.091239 0.006169 0.606052 -#> 011: 0.453442 0.853622 3.427827 0.351512 0.086620 0.006578 0.608115 -#> 012: 0.462225 0.853917 3.425827 0.361433 0.082071 0.006803 0.605303 -#> 013: 0.458003 0.859284 3.422302 0.375770 0.078209 0.006864 0.609796 -#> 014: 0.463493 0.859918 3.421436 0.394293 0.077441 0.007209 0.612385 -#> 015: 0.461922 0.861117 3.422084 0.391491 0.075832 0.007177 0.610504 -#> 016: 0.463641 0.860191 3.423481 0.388623 0.072947 0.007093 0.610327 -#> 017: 0.466608 0.861250 3.424922 0.387369 0.071245 0.007120 0.609212 -#> 018: 0.467115 0.863905 3.424010 0.385711 0.070812 0.007068 0.607741 -#> 019: 0.464636 0.865482 3.423091 0.384225 0.070733 0.006891 0.605629 -#> 020: 0.466311 0.867835 3.422920 0.388178 0.071830 0.006899 0.603946 -#> 021: 0.467791 0.867667 3.423117 0.388788 0.072470 0.006804 0.603274 -#> 022: 0.467680 0.867848 3.423223 0.389921 0.072747 0.006679 0.601932 -#> 023: 0.471964 0.867613 3.423780 0.392002 0.073413 0.006733 0.601413 -#> 024: 0.471012 0.869247 3.423531 0.391023 0.074191 0.006624 0.600971 -#> 025: 0.471592 0.868571 3.423338 0.394052 0.075357 0.006510 0.600329 -#> 026: 0.470657 0.869562 3.423072 0.395694 0.076004 0.006495 0.600176 -#> 027: 0.469108 0.870772 3.422378 0.395820 0.076448 0.006516 0.600126 -#> 028: 0.467693 0.871474 3.422045 0.393456 0.075655 0.006647 0.599299 -#> 029: 0.468393 0.872718 3.421465 0.391148 0.075150 0.006719 0.599974 -#> 030: 0.468304 0.873833 3.420865 0.390229 0.075320 0.006836 0.599273 -#> 001: 0.321454 0.971377 3.443146 0.381052 0.077198 0.016351 1.843240 -#> 002: 0.404381 0.984655 3.454425 0.361999 0.073338 0.015533 1.327013 -#> 003: 0.524777 0.923516 3.448166 0.343899 0.069671 0.014757 0.973899 -#> 004: 0.464318 0.918715 3.444206 0.326704 0.066188 0.014019 0.899000 -#> 005: 0.505866 0.944304 3.428324 0.369671 0.075402 0.013318 0.849983 -#> 006: 0.463863 0.956021 3.409451 0.351188 0.087264 0.012652 0.825540 -#> 007: 0.428948 0.950593 3.414305 0.333628 0.085637 0.012019 0.835024 -#> 008: 0.421492 0.943008 3.403544 0.316947 0.086564 0.012203 0.836564 -#> 009: 0.393406 0.940308 3.406897 0.301100 0.083656 0.014303 0.847300 -#> 010: 0.441726 0.936843 3.412050 0.258291 0.089442 0.013228 0.846843 -#> 011: 0.463308 0.937482 3.413063 0.248330 0.094996 0.012282 0.848071 -#> 012: 0.453256 0.941789 3.410521 0.245399 0.103340 0.011370 0.838674 -#> 013: 0.440268 0.949914 3.407022 0.233480 0.106164 0.010496 0.837572 -#> 014: 0.443334 0.949030 3.408971 0.243138 0.108268 0.010403 0.840363 -#> 015: 0.447580 0.948484 3.410579 0.244311 0.107791 0.010531 0.837262 -#> 016: 0.446239 0.951883 3.411966 0.243853 0.107251 0.010434 0.835515 -#> 017: 0.446532 0.954138 3.413003 0.246637 0.106016 0.010641 0.836453 -#> 018: 0.446437 0.956413 3.411380 0.244549 0.106120 0.010611 0.836756 -#> 019: 0.440359 0.957282 3.410359 0.246071 0.106063 0.010584 0.837482 -#> 020: 0.438193 0.958720 3.410340 0.248115 0.108699 0.010520 0.836311 -#> 021: 0.438664 0.958757 3.410299 0.247831 0.110066 0.010608 0.834780 -#> 022: 0.438099 0.958202 3.411346 0.251382 0.111559 0.010467 0.834395 -#> 023: 0.442660 0.957814 3.412045 0.250540 0.111833 0.010353 0.835423 -#> 024: 0.445029 0.959311 3.412104 0.252011 0.112183 0.010420 0.836493 -#> 025: 0.445302 0.957116 3.412285 0.252143 0.111216 0.010417 0.837473 -#> 026: 0.445494 0.959271 3.411336 0.254985 0.111211 0.010295 0.836981 -#> 027: 0.442450 0.961509 3.410295 0.255564 0.111479 0.010272 0.836688 -#> 028: 0.442704 0.961873 3.410156 0.257600 0.110936 0.010306 0.835889 -#> 029: 0.443796 0.962325 3.409781 0.257516 0.111795 0.010518 0.835939 -#> 030: 0.444443 0.962669 3.409480 0.259052 0.111135 0.010623 0.836011 -#> 001: 0.308790 0.955292 3.452306 0.381052 0.078745 0.016351 1.610290 -#> 002: 0.320194 0.972929 3.441237 0.361999 0.074808 0.015533 1.052149 -#> 003: 0.388375 0.903049 3.451275 0.343899 0.071067 0.014757 0.876051 -#> 004: 0.352724 0.943163 3.446667 0.326704 0.067514 0.014019 0.848090 -#> 005: 0.370729 0.942207 3.437666 0.310369 0.064138 0.013318 0.811039 -#> 006: 0.340865 0.946849 3.433523 0.294850 0.067188 0.012652 0.778070 -#> 007: 0.321317 0.929801 3.430701 0.280108 0.078825 0.012019 0.807483 -#> 008: 0.297800 0.954520 3.419284 0.266103 0.074883 0.012974 0.812512 -#> 009: 0.268345 0.941798 3.412954 0.252797 0.071139 0.012325 0.820797 -#> 010: 0.284470 0.945655 3.410890 0.167484 0.058407 0.009044 0.819982 -#> 011: 0.304119 0.956041 3.413440 0.160651 0.058828 0.009528 0.823598 -#> 012: 0.310049 0.953562 3.414981 0.158940 0.058257 0.009152 0.821713 -#> 013: 0.294795 0.958102 3.411723 0.154670 0.062969 0.009092 0.826275 -#> 014: 0.295332 0.962803 3.410459 0.150207 0.064431 0.008887 0.830045 -#> 015: 0.299234 0.965921 3.411482 0.147028 0.065119 0.008854 0.828014 -#> 016: 0.296557 0.968780 3.412439 0.142049 0.062697 0.008819 0.829825 -#> 017: 0.301181 0.968624 3.412841 0.141986 0.063694 0.008653 0.829478 -#> 018: 0.302265 0.969492 3.411867 0.141653 0.063770 0.008469 0.831797 -#> 019: 0.297096 0.971173 3.411014 0.139000 0.063844 0.008428 0.832478 -#> 020: 0.295719 0.970786 3.411676 0.136934 0.062973 0.008331 0.832896 -#> 021: 0.296313 0.970269 3.412745 0.133780 0.062369 0.008326 0.832039 -#> 022: 0.295929 0.968986 3.413278 0.131895 0.062932 0.008154 0.831096 -#> 023: 0.300475 0.969702 3.413923 0.132320 0.063767 0.007973 0.830692 -#> 024: 0.305282 0.970974 3.414907 0.132679 0.064361 0.007801 0.829612 -#> 025: 0.305960 0.970655 3.415266 0.134425 0.064468 0.007752 0.828770 -#> 026: 0.305518 0.972429 3.414596 0.133795 0.064520 0.007710 0.829005 -#> 027: 0.305864 0.972931 3.415149 0.133015 0.064204 0.007695 0.829063 -#> 028: 0.305834 0.973216 3.414863 0.132775 0.064447 0.007567 0.828023 -#> 029: 0.307110 0.972875 3.414641 0.134106 0.064937 0.007559 0.827898 -#> 030: 0.308437 0.973293 3.414467 0.134239 0.065239 0.007624 0.827103 -#> 001: 0.250224 0.973350 3.446505 0.381052 0.086079 0.016351 1.629574 -#> 002: 0.238043 0.945447 3.463598 0.361999 0.081775 0.015533 1.148022 -#> 003: 0.302269 0.841802 3.468763 0.343899 0.090469 0.014757 0.857538 -#> 004: 0.243896 0.865882 3.459904 0.326704 0.111023 0.014019 0.756165 -#> 005: 0.282010 0.882191 3.454090 0.310369 0.138965 0.013318 0.732686 -#> 006: 0.222474 0.885134 3.439456 0.294850 0.137408 0.013019 0.659474 -#> 007: 0.205525 0.892145 3.433143 0.280108 0.159956 0.013598 0.644376 -#> 008: 0.196289 0.882056 3.422450 0.266103 0.151958 0.016950 0.625512 -#> 009: 0.154722 0.867262 3.413034 0.252797 0.153009 0.016616 0.622420 -#> 010: 0.161861 0.886435 3.409333 0.179466 0.147778 0.015684 0.616576 -#> 011: 0.178851 0.885066 3.414862 0.190479 0.150189 0.016168 0.613058 -#> 012: 0.192803 0.891881 3.415838 0.197485 0.142894 0.016087 0.612558 -#> 013: 0.179534 0.903459 3.410968 0.187154 0.138015 0.016358 0.610325 -#> 014: 0.186389 0.904350 3.413515 0.184616 0.140652 0.016013 0.611363 -#> 015: 0.191013 0.904880 3.416840 0.180732 0.138288 0.016149 0.607843 -#> 016: 0.194851 0.906830 3.417924 0.179089 0.136730 0.017363 0.605451 -#> 017: 0.196487 0.907656 3.418840 0.179106 0.134246 0.017928 0.602876 -#> 018: 0.199138 0.909915 3.418241 0.180375 0.132986 0.018225 0.601193 -#> 019: 0.195281 0.910217 3.417478 0.181078 0.133218 0.018439 0.601077 -#> 020: 0.193751 0.911645 3.417332 0.179321 0.132558 0.018496 0.600899 -#> 021: 0.195542 0.912633 3.418240 0.178133 0.131680 0.018178 0.600791 -#> 022: 0.196856 0.913167 3.419484 0.176285 0.131776 0.018081 0.600220 -#> 023: 0.201760 0.912215 3.420795 0.178293 0.131133 0.018055 0.599618 -#> 024: 0.206143 0.911332 3.421689 0.180024 0.130477 0.018251 0.598885 -#> 025: 0.208976 0.909441 3.422674 0.181317 0.128259 0.018617 0.598188 -#> 026: 0.209246 0.909773 3.422754 0.182192 0.127371 0.018828 0.597104 -#> 027: 0.210086 0.911391 3.422127 0.185631 0.126914 0.019049 0.596365 -#> 028: 0.210242 0.912131 3.422173 0.187723 0.125802 0.019472 0.595784 -#> 029: 0.211096 0.912247 3.421602 0.191255 0.124943 0.019610 0.595855 -#> 030: 0.211086 0.912450 3.421134 0.193390 0.125181 0.019772 0.595781 fit2 -#> ── nlmixr² SAEM OBJF by FOCEi approximation ── -#> -#> Gaussian/Laplacian Likelihoods: AIC(fit) or fit$objf etc. -#> FOCEi CWRES & Likelihoods: addCwres(fit) -#> -#> ── Time (sec fit$time): ── -#> -#> setup covariance saem table compress other -#> elapsed 0.001 7.18 3.2 0.07 0.08 4.129 -#> -#> ── Population Parameters (fit$parFixed or fit$parFixedDf): ── -#> -#> Parameter Est. SE %RSE Back-transformed(95%CI) BSV(CV%) -#> tka Log Ka 0.459 0.127 27.8 1.58 (1.23, 2.03) 70.2 -#> tcl Log Cl 1.01 0.0895 8.85 2.75 (2.31, 3.28) 27.7 -#> tv Log V 3.45 0.034 0.985 31.6 (29.6, 33.8) 13.2 -#> add.sd 0.696 0.696 -#> Shrink(SD)% -#> tka -5.46% -#> tcl 0.387% -#> tv 13.8% -#> add.sd -#> -#> Covariance Type (fit$covMethod): boot5 -#> other calculated covs (setCov()): linFim -#> No correlations in between subject variability (BSV) matrix -#> Full BSV covariance (fit$omega) or correlation (fit$omegaR; diagonals=SDs) -#> Distribution stats (mean/skewness/kurtosis/p-value) available in fit$shrink -#> Censoring (fit$censInformation): No censoring -#> -#> ── Fit Data (object fit is a modified tibble): ── -#> # A tibble: 132 × 19 -#> ID TIME DV PRED RES IPRED IRES IWRES eta.ka eta.cl eta.v cp -#> -#> 1 1 0 0.74 0 0.74 0 0.74 1.06 0.143 -0.439 -0.0982 0 -#> 2 1 0.25 2.84 3.27 -0.430 4.06 -1.22 -1.75 0.143 -0.439 -0.0982 4.06 -#> 3 1 0.57 6.57 5.85 0.721 7.08 -0.508 -0.731 0.143 -0.439 -0.0982 7.08 -#> # … with 129 more rows, and 7 more variables: depot , center , -#> # ka , cl , v , tad , dosenum ```