README.Rmd

---
output: github_document
---

<!-- README.md is generated from README.Rmd. Please edit that file -->

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)
```

# nlmixr2plot: The core estimation routines for nlmixr2

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The goal of nlmixr2plot is to provide the nlmixr2 core estimation routines.

## Installation

You can install the development version of nlmixr2plot from [GitHub](https://github.com/) with:

``` r
# 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.

```{r example}
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)
```