README.Rmd

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

# RxODE

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## Overview

**RxODE** is an R package for solving and simulating from ode-based
models. These models are convert the RxODE mini-language to C and
create a compiled dll for fast solving. ODE solving using RxODE has a
few key parts:

 - `RxODE()` which creates the C code for fast ODE solving based on a
   [simple syntax](https://nlmixrdevelopment.github.io/RxODE/articles/RxODE-syntax.html) related to Leibnitz notation.
 - The event data, which can be:
   - a `NONMEM` or `deSolve` [compatible data frame](https://nlmixrdevelopment.github.io/RxODE/articles/RxODE-event-types.html), or
   - created with `et()` or `EventTable()` for [easy simulation of events](https://nlmixrdevelopment.github.io/RxODE/articles/RxODE-event-table.html)
   - The data frame can be augmented by adding
     [time-varying](https://nlmixrdevelopment.github.io/RxODE/articles/RxODE-covariates.html#time-varying-covariates)
     or adding [individual covariates](https://nlmixrdevelopment.github.io/RxODE/articles/RxODE-covariates.html#individual-covariates) (`iCov=` as needed)
 - `rxSolve()` which solves the system of equations using initial
   conditions and parameters to make predictions
   - With multiple subject data, [this may be
     parallelized](https://nlmixrdevelopment.github.io/RxODE/articles/RxODE-speed.html).
   - With single subject the [output data frame is adaptive](https://nlmixrdevelopment.github.io/RxODE/articles/RxODE-data-frame.html)
   - Covariances and other metrics of uncertanty can be used to
     [simulate while solving](https://nlmixrdevelopment.github.io/RxODE/articles/RxODE-sim-var.html)

## Installation

```{r child='man-roxygen/rmdhunks/RxODE-install-hunk.Rmd'}
```

# Illustrated Example

```{r child='man/rmdhunks/RxODE-intro-chunk.Rmd'}
```

# Related R Packages
```{r child='man-roxygen/rmdhunks/related-R-chunk.Rmd'}
```