1. Request Reply Protocol | 2. Publisher Subscriber Protocol | 3. Surveyor Respondent Protocol | 4. Device (Broker / Proxy)

1. Migration from future_promise() | 2. Setting the random seed | 3. Accessing package functions during development | 4. Why does mirai() take time when it's meant to return immediately? | 5. Creating daemons on-demand or shutting down idle daemons | 6. Launching daemons --vanilla

1. Agent Skill | 2. Developer Interfaces | 3. Guidance

1. Introduction | mirai | mirai (advanced) | daemons | 2. Error Handling | 3. Local Daemons | With Dispatcher (default) | Without Dispatcher | everywhere() | 4. Memory Management | Queue Backpressure | Non-blocking Submission | Shared Memory with Local Daemons | 5. mirai_map | Basic Usage | Collection Options | Multiple Map | Nested Maps | 6. Remote Infrastructure | Remote Daemons Overview | Launching Remote Daemons | SSH Direct Connection | SSH Tunnelling | HPC Cluster Resource Managers | Job Arrays | HTTP Launcher | Default: Posit Workbench | Custom HTTP APIs | Troubleshooting | Generic Remote Configuration | Manual Deployment | TLS Secure Connections | Automatic Zero-configuration Default | CA Signed Certificates | 7. Compute Profiles | with_daemons() and local_daemons() | With Method | 8. Advanced Topics | Random Number Generation | Synchronous Mode

Core Concepts | Key Takeaways | 1. Basic mirai Usage | Create and Access Results | Passing Data | 2. Local Daemons | Basic Setup | Daemon Configuration | Synchronous Mode (Testing/Debugging) | 3. Remote Daemons - SSH Direct | Setup Host to Accept Remote Connections | URL Constructors | SSH Configuration | 4. Remote Daemons - SSH Tunnelling | When to Use Tunnelling | Setup | 5. HPC Cluster Configurations | General Pattern | Scheduler-Specific Directives | 6. HTTP Launcher | 7. Manual Daemon Deployment | Generate Launch Commands | 8. Compute Profiles | Multiple Independent Profiles | Scoped Profiles | 9. Common Patterns | Temporary Daemons | Mixed Local/Remote Resources | Dynamic Scaling | 10. mirai_map - Parallel Map | Basic Usage | Collection Options | Multiple Map (over DataFrame/Matrix) | 11. Error Handling | 12. Monitoring | 13. Advanced Features | Timeouts | Cancellation | Evaluation Everywhere | Random Seeds (Reproducible) | Custom Serialization | TLS Configuration | 14. Dispatcher vs. Direct | 15. Quick Decision Tree | 16. Common Gotchas

Data of the current study | Benchmark analysis with a diffuse prior | Constructing the robust MAP prior | Converting the prior for use in brms.mmrm | Fitting the Bayesian MMRM with the MAP prior | Multivariate mixture priors | Specifying a known prior | Constructing a prior from real data | References

How it works | Parallel functional programming | Asynchronous parallel functional programming | Auto-scaling | Caveats and limitations

Logging worker processes | In targets

Tasks vs workers | How to use crew | Synchronous functional programming | Asynchronous functional programming | Summaries | Termination | Monitoring local processes | Tuning and auto-scaling | Crashes and retries

Resource usage | Workers | Crashes | Ports | Security | Perimeters | Encryption | Certificate authorities

About | How it works | Scope | Implementation | Network | Example | Batched launches | Controllers | Informal testing | Load testing | Managing workers

1. HTTP Client | ncurl: Basic Requests | ncurl_aio: Async Requests | Promises Integration | ncurl_session: Persistent Connections | 2. WebSocket Client | 3. Unified HTTP/WebSocket Server | Handler Types | HTTP Request Handlers | Static Content Handlers | WebSocket Handlers | HTTP Streaming Handlers | Server-Sent Events | 4. Secure Connections (TLS) | Public Internet HTTPS | Self-Signed Certificates | 5. Client Example: Shiny ExtendedTask | 6. Server Example: Quarto Site with Dynamic API

1. Event-driven promises | 2. Shiny ExtendedTask: Introduction | 3. Shiny ExtendedTask: Cancellation | 4. Shiny ExtendedTask: Generative Art | 5. Shiny ExtendedTask: mirai map | 6. Shiny Async: Coin Flips | 7. Shiny Async: Progress Bar | 8. Plumber GET Endpoint | 9. Plumber POST Endpoint

Core Concepts | Key Takeaways | 1. Sockets and Connections | Create Sockets | Protocols | Transports | 2. Send and Receive | Synchronous | Receive Modes | 3. Async I/O | Basic Async | Non-blocking Patterns | 4. Condition Variables | Basics | Pipe Notifications | Async with CV | 5. Request/Reply (RPC) | Server | Client | 6. Pub/Sub | 7. Surveyor/Respondent | 8. TLS Secure Connections | Self-signed Certificates | CA Certificates | 9. Options and Statistics | Get/Set Options | Common Options | Custom Serialization | Statistics | 10. Contexts | 11. Cross-language Exchange | R to Python (NumPy) | 12. Error Handling | 13. Utilities

1. TLS Secure Connections | 2. Options | 3. Custom Serialization | 4. Statistics

1. Cross-language Exchange | 2. Async and Concurrency | 3. Synchronisation Primitives

Implementation | Last run | Convergence | Parameter coverage

Raw data | Models | Checking and troubleshooting | Summaries | Marginals | Predictions | Plots

Common elements | Data | Likelihood | Variance | Expected value of the control group | The decline models | The non-proportional decline model | The proportional decline model | The slowing models | The non-proportional slowing model | The proportional slowing model | References

1. Mirai Parallel Clusters | 2. Foreach Support

1. Introduction | 2. Automatic Tracing Setup | 3. Span Types and Hierarchy | 3.1 Core Span Types | 3.2 Span Relationships and Context Propagation | 4. Status and Error Tracking | 5. Monitoring and Observability | 6. Integration with Observability Platforms

1. Serialization: Arrow, polars and beyond | 2. Serialization: Torch | 3. Database Hosting using Arrow Database Connectivity | 4. Shiny / mirai / DBI / ADBC Integrated Example

Multiple models | Generated quantities | More information

Constructing an archetype | Informative priors | Modeling and analysis | All archetypes | Variations on archetypes

About | Example: coin flips, no promises | Tutorial | Full app code | Example: coin flips, with promises

Backup controllers

Example data | Marginal means for clinical trials | Existing capabilities | How brms.mmrm estimates marginal means | How brm_marginal_draws() works | Subgroup analysis | References

Priors | Sampling | Imputation of missing outcomes | References

Raw data | Preprocessing | Formula | Priors | Model | Marginals | Visualization | Comparing models and data | Plotting draws | Comparing priors and posteriors | Appendix A: Contrasts | Appendix B: Imputation of missing outcomes | Imputation before model fitting | Imputation during model fitting | References

Simple | Change from baseline | Advanced | Prior | Posterior

About | Prerequisites | Data | Pre-processing | Descriptive statistics | Fitting MMRMs | Bayesian model | Frequentist model | Comparison | Extract estimates from Bayesian model | Extract estimates from frequentist model | Summary

About | Prerequisites | Data | Pre-processing | Descriptive statistics | Fitting MMRMs | Bayesian model | Frequentist model | Comparison | Extract estimates from Bayesian model | Extract estimates from frequentist model | Summary | Session info

Data | Formula | Models | Marginals | Model comparison | Visualization | References

About | Conclusion | Setup | Subgroup scenario | Unstructured scenario | Autoregressive moving average scenario | Autoregressive scenario | Moving average scenario | Compound symmetry scenario | Diagonal scenario | References

Background | Example project | Interval-based model validation pipeline | Multiple models | Simulation-based calibration | References

What is targets? | How to get started | The walkthrough | Help | Debugging | Functions | Target construction | Packages | Projects | Data and files | Literate programming | Distributed computing | Performance | Dynamic branching | Static branching

What is targets? | How to get started | The walkthrough | Help | Debugging | Functions | Target construction | Packages | Projects | Data and files | Literate programming | Distributed computing | Performance | Dynamic branching | Static branching

Installation | Remotes | Overall workflow | Create code | Run pipeline | Commit code | Snapshot data | Snapshot model | Repeat | View log | Check out code | Check out data | Merges | Custom data files | Performance

Multiple models | References

Multiple models | More information

FACTS XML format | Write FACTS files | Check your work

System dependency specification file | Required columns | Connecting rfacts to the system dependencies

How it works | Test locally first | On a cluster