Registering a stochastic simulation function | Registering at package load time | Integrating stochastic estimation methods | When to use each integration path | Practical limitations

Why save a fit this way? | What gets restored? | Dataset-aware caching | 1. Irrelevant dataset changes do not force a refit | 2. Meaningful dataset changes do force a refit | Using := for long-running fits and simulations | Seed-aware restores for stochastic work | Integrating nlmixr2save into your package | Deterministic estimation | Stochastic estimation or simulation | Limitations

Registering a stochastic simulation function | Registering at package load time | Integrating stochastic estimation methods | When to use each integration path | Practical limitations

Why save a fit this way? | What gets restored? | Dataset-aware caching | 1. Irrelevant dataset changes do not force a refit | 2. Meaningful dataset changes do force a refit | Using := for long-running fits and simulations | Seed-aware restores for stochastic work | Integrating nlmixr2save into your package | Deterministic estimation | Stochastic estimation or simulation | Limitations

Introduction | Creating rxode2 models | Syntax | Note | Example model | Example | Interface and data handling between R and the generated C code

Setting up nonmem2rx for your model | Technical details about reading NONMEM to rxode2

Abstract | Provenance of the R optim::L-BFGS-B and related solvers | Functions in package lbfgsb3c | Candlestick function | Extended Rosenbrock function (from funconstrain) | Using compiled function code | References

Motivation | Creating lists of matrices with attached properties | Combining symmetric named matrices