bm <- load_benchmark_dataset(“BM_Canonical_HighSNR”)

Create an event model

events <- bm $core_data$ event_table sframe <- sampling_frame(blocklens = bm $core_data$ run_length, TR = bm $core_data$ TR) emod <- event_model(onset ~ hrf(condition), data = events, block = ~run, sampling_frame = sframe)

Fit the model

fit <- fmri_lm(emod, dataset = bm$core_data)


## Documentation

See comprehensive examples and tutorials in the [vignettes](https://bbuchsbaum.github.io/fmrireg/articles/index.html):

- [Hemodynamic Response Functions](https://bbuchsbaum.github.io/fmrireg/articles/a_01_hemodynamic_response.html)
- [Building Regressors](https://bbuchsbaum.github.io/fmrireg/articles/a_02_regressor.html)
- [Event Models](https://bbuchsbaum.github.io/fmrireg/articles/a_04_event_models.html)
- [Statistical Contrasts](https://bbuchsbaum.github.io/fmrireg/articles/a_05_contrasts.html)
- [Linear Modeling](https://bbuchsbaum.github.io/fmrireg/articles/a_09_linear_model.html)

## Performance Configuration

The internal C++ routines use [RcppParallel](https://rcppcore.github.io/RcppParallel/). You can control the number of threads by setting the R option `fmrireg.num_threads` or the environment variable `FMRIREG_NUM_THREADS` before loading the package. If either is set, `fmrireg` calls `RcppParallel::setThreadOptions()` when it loads.

## Development Status

`fmrireg` is currently in active development. While the core functionality is stable, the API may change as we continue to improve the package. Please [file issues](https://github.com/bbuchsbaum/fmrireg/issues) for bugs or feature requests.

## Citation

If you use `fmrireg` in your research, please cite:

Buchsbaum, B. R. (2024). fmrireg: fMRI Analysis in R. R package version 0.1.0. https://github.com/bbuchsbaum/fmrireg ```