01-intro.Rmd

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# Introduction {#index}

Welcome to the rxode2 user guide; **rxode2** is an R package for solving
and simulating from ode-based models. These models are convert the rxode2
mini-language to C and create a compiled dll for fast solving. ODE
solving using rxode2 has a few key parts:

-   `rxode2()` which creates the C code for fast ODE solving based on a
    simple syntax (Chapter \@ref(syntax)) related to Leibnitz notation.

-   The event data, which can be:

    -   a `NONMEM` or `deSolve` compatible data frame (Chapter
        \@ref(events)), or
    -   created with `et()` or `EventTable()` for easy simulation of
        events (Chapter \@ref(simulation))
    -   The data frame can be augmented by adding time varying or adding
        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.
    -   With single subject the output data frame is adaptive
    -   Covariances and other metrics of uncertainty can be used to
        simulate while solving.

While this is the user guide, there are other places that you can visit
for help:

-   `rxode2` github [pkgdown
    page](https://nlmixr2.github.io/rxode2/)
-   `rxode2` tutorial (accessible in tutorials in Rstudio 1.3+)
-   `rxode2` [github
    discussions](https://github.com/nlmixr2/rxode2/discussions)
    
- There is an [Chinese `rxode2` manual translated by Fu
  Yongchao](https://s0521.github.io/rxode2_chs/) which was translated
  based on the manual dated June 9, 2023.

This book was assembled on `r date()` with rxode2 version
`r packageVersion("rxode2")` automatically by github actions.

# Authors and Acknowledgments {#author}

```{r introAuthors, echo=FALSE, results='asis'}
cat(paste(gsub("^#", "##", readLines('rxode2/authors.md')), collapse="\n"), "\n\n")
```

# Related R packages {#related}

```{r introRelated, child='rxode2/man-roxygen/rmdhunks/related-R-chunk.Rmd'}
```