knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.path = "man/figures/README-", out.width = "100%" )
The goal of nlmixr2plot is to provide the nlmixr2 core estimation routines.
You can install the development version of nlmixr2plot from GitHub with:
# install.packages("remotes") remotes::install_github("nlmixr2/nlmixr2data") remotes::install_github("nlmixr2/lotri") remotes::install_github("nlmixr2/rxode2") remotes::install_github("nlmixr2/nlmixr2est") remotes::install_github("nlmixr2/nlmixr2extra") remotes::install_github("nlmixr2/nlmixr2plot")
For most people, using nlmixr2 directly would be likely easier.
library(nlmixr2est) library(nlmixr2plot) ## The basic model consists of an ini block that has initial estimates one.compartment <- function() { ini({ tka <- 0.45 ; label("Log Ka") tcl <- 1 ; label("Log Cl") tv <- 3.45 ; label("Log V") eta.ka ~ 0.6 eta.cl ~ 0.3 eta.v ~ 0.1 add.sd <- 0.7 }) # and a model block with the error specification and model specification model({ ka <- exp(tka + eta.ka) cl <- exp(tcl + eta.cl) v <- exp(tv + eta.v) d/dt(depot) = -ka * depot d/dt(center) = ka * depot - cl / v * center cp = center / v cp ~ add(add.sd) }) } ## The fit is performed by the function nlmixr/nlmix2 specifying the model, data and estimate fit <- nlmixr2(one.compartment, theo_sd, est="saem", saemControl(print=0)) print(fit) # this now gives the goodness of fit plots plot(fit)
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