This release adds support for a wider range of distributions in the marginal model, improves documentation with new vignettes and FAQ sections, enhances the getting started guide with clearer examples of model comparison, and fixes several bugs related to parameter bounds and likelihood calculations. ## Models - Added Stan-side support for fitting all distributions supported by `primarycensored` in the marginal model. See #540. - Added R-side analytical likelihood support for Lognormal, Gamma, and Weibull distributions. See #540. ## Package - Remove caching of vignettes. See #533. ## Documentation - Added a new vignette "Guide to the statistical models implemented in epidist". See #514. - Added a new FAQ section showcasing how to use the `posterior` package with `epidist` models, particularly for working with random variables (`rvars`) to propagate uncertainty in calculations. See #547. - Added a new FAQ section on how to use the `marginaleffects` package with `epidist` models. See #547. - Reduced the focus on simulating data in the getting started vignette to make it more accessible. See #549. - Made the entry to the package friendlier with clearer examples and improved documentation. See #549. - Added a schematic to explain right truncation more clearly to the getting started vignette. See #549. - Added a comparison of fitting naive and marginal models in the getting started vignette to highlight the importance of accounting for biases. See #549. - Added examples showing how to extract estimated parameters and plot them against true values to evaluate model performance. See #549. ## Bugs - Fixed a vector length issue for censoring that was causing problems in some likelihood calls. See #540. - Fixed a bug in the preprocessing of the Weibull family. See #540. - Fixed a bug where bounds were not set for mu parameters in custom families. See #549. - Fixed a bug in `predict_delay_parameters()` where it couldn't detect brms families when used directly. See #549. ## What's Changed * Update _pkgdown.yml - add news by @seabbs in https://github.com/epinowcast/epidist/pull/527 * Small typo by @athowes in https://github.com/epinowcast/epidist/pull/528 * Bump codecov/codecov-action from 4 to 5 by @dependabot in https://github.com/epinowcast/epidist/pull/531 * Issue #532: Remove caching by @seabbs in https://github.com/epinowcast/epidist/pull/533 * Issue #64: Add vignette explaining models by @parksw3 in https://github.com/epinowcast/epidist/pull/514 * Issue #477: Add analytical likelihoods to R functionality by @seabbs in https://github.com/epinowcast/epidist/pull/540 * Bump JamesIves/github-pages-deploy-action from 4.7.1 to 4.7.3 by @dependabot in https://github.com/epinowcast/epidist/pull/542 * Issue #544: fixing minor typos in 2 vignettes by @cherz4 in https://github.com/epinowcast/epidist/pull/545 * Update README by @github-actions in https://github.com/epinowcast/epidist/pull/546 * Issue #468: Add marginaleffects and rvars to the FAQ by @seabbs in https://github.com/epinowcast/epidist/pull/547 * Issue #548: Refactor the getting started vignette by @seabbs in https://github.com/epinowcast/epidist/pull/549 * Update README by @github-actions in https://github.com/epinowcast/epidist/pull/551 ## New Contributors * @cherz4 made their first contribution in https://github.com/epinowcast/epidist/pull/545 **Full Changelog**: https://github.com/epinowcast/epidist/compare/v0.2.0...v0.3.0

This release adds a new marginal model based on `primarycensored` which provides a more efficient approach for fitting delay distributions compared to the existing latent model. We've also improved data handling by adding support for aggregated data across all models, added comprehensive examples using real world data, and enhanced documentation based on user feedback. The package has also undergone significant internal improvements including generalised Stan reparameterisation and improved data transformation methods. As part of this release, we have moved from @athowes maintaining the package (who led the initial package development, implementation of the S3 infrastructure, implementation of the core models, and wrote the first versions of the getting started vignette, Ebola case study, FAQ section, and the approximate inference vignette) to @seabbs maintaining the package. ## Models - Added a marginalised likelihood model based on `primarycensored`. This can be specified using `as_epidist_marginal_model()`. This is currently limited to Weibull, log-normal, and gamma distributions with uniform primary censoring but this will be generalised in future releases. See #426. - Added user settable primary event priors to the latent model. See #474. - Added a marginalised likelihood to the latent model. See #474. - Added a `weight` argument to `as_epidist_marginal_model()` to allow for weighted data (for example count data) to be used in the marginal model. See #509. - Added a `epidist_aggregate_data` method to `as_epidist_marginal_model()` to allow straightforward use of the marginal model with aggregated data. See #510. - Added a `epidist_aggregate_data` method to `as_epidist_latent_model()` to allow straightforward use of the latent model with aggregated data. See #510. - Added a `epidist_aggregate_data` method to `as_epidist_naive_model()` to allow straightforward use of the naive model with aggregated data. See #510. - Updated the naive model to internally transform the data to be optimally aggregated as for the marginal model. See #510. ## Package - Remove the default method for `epidist()`. See #473. - Added `enforce_presence` argument to `epidist_prior()` to allow for priors to be specified if they do not match existing parameters. See #474. - Added a `merge` argument to `epidist_prior()` to allow for not merging user and package priors. See #474. - Generalised the Stan reparametrisation feature to work across all distributions without manual specification by generating Stan code with `brms` and then extracting the reparameterisation. See #474. - Added a `transform_data` S3 method to allow for data to be transformed for specific models. This is specifically useful for the marginal model at the moment as it allows reducing the data to its unique strata. See #474. - Added new `epidist_aggregate_data` class to handle pre-aggregated line list data. See #510. - Added a `as_epidist_aggregate_data()` method for `epidist_linelist_data` objects to allow for easy conversion to aggregate data. See #510. - Added a `as_epidist_linelist_data()` method for `epidist_aggregate_data` objects to allow for easy conversion to linelist data. See #510. - Added an example dataset `sierra_leone_ebola_data` to the package. See #510. - Added examples to most functions to show usage of the package. See #510. - Added improved documentation explaining how the `epidist_transform_data()` methods work for the marginal and naive models. See #510. ## Documentation - Brings the README into line with `epinowcast` standards. See #467. - Switched over to using the marginal model as default in the documentation. See #426. - Added a helper functions for new variables to avoid code duplication in vignettes. See #426. - Improved the Ebola case study vignette to use truncated data and to reduce the focus on exploratory data analysis. See #510. ## Bugs - Switched to using a patched of `primarycensored` that doesn't make use of `size()`. This fixes some Mac compilation edge cases. See #524. ## Pull requests * Update README by @github-actions in https://github.com/epinowcast/epidist/pull/506 * Issue #507: Add weighting support to marginal model class by @seabbs in https://github.com/epinowcast/epidist/pull/509 * Update README by @github-actions in https://github.com/epinowcast/epidist/pull/511 * Issue #503: Fix windows CI by @seabbs in https://github.com/epinowcast/epidist/pull/517 * fix typo by @sbfnk in https://github.com/epinowcast/epidist/pull/518 * fix typo by @sbfnk in https://github.com/epinowcast/epidist/pull/519 * Add @sbfnk as contributor by @seabbs in https://github.com/epinowcast/epidist/pull/520 * Update README by @github-actions in https://github.com/epinowcast/epidist/pull/522 * Issue #504: Use patched primarycensored without size() by @seabbs in https://github.com/epinowcast/epidist/pull/524 * Issue #521: Change maintainer by @seabbs in https://github.com/epinowcast/epidist/pull/525 * Issue #508: Aggregate data class by @seabbs in https://github.com/epinowcast/epidist/pull/513 ## New Contributors * @sbfnk made their first contribution in https://github.com/epinowcast/epidist/pull/518 **Full Changelog**: https://github.com/epinowcast/epidist/commits/v0.2.0

# epidist 0.1.0 This is the first minor release of `epidist` intended for early test users of the package. As some features may change, the package is marked as experimental. We expect to release a stable 1.0.0 version shortly. The `epidist` package implements models for epidemiological delay distributions. It uses [`brms`](http://paulbuerkner.com/brms/) to perform Bayesian inference. One data format is currently available: 1. The [linelist data](https://epidist.epinowcast.org/reference/index.html#linelist-data) format Two statistical models are currently available: 1. The [naive model](https://epidist.epinowcast.org/reference/index.html#naive-model): which models the delay directly using `brms` 2. The [latent model](https://epidist.epinowcast.org/reference/index.html#latent-model): which implements a latent variable model to correct for biases in the data The package is readily extensible to additional models via an [S3](https://adv-r.hadley.nz/s3.html) class based system. In particular, model fitting with [epidist()] is possible using S3 classes for custom: 1. [Families](https://epidist.epinowcast.org/reference/index.html#family) 2. [Formula](https://epidist.epinowcast.org/reference/index.html#formula) 3. [Prior distributions](https://epidist.epinowcast.org/reference/index.html#prior-distributions) 4. [Stan code](https://epidist.epinowcast.org/reference/index.html#stan-code) We provide functionality for [post-processing](https://epidist.epinowcast.org/reference/index.html#postprocess). Alternatively, users may directly use `tidybayes` for specific families. Three vignettes are available. There is also a [frequently asked questions](https://epidist.epinowcast.org/articles/faq.html) website section.