Changelog

Added step function to toolkit to allow for brms non-linear formula evaluation (89edef72).

Fixed issues with summary and print methods (bf058f36).
Plotting methods now display the proper no-effect toxicity legend label (2be55d51).
Implemented native brms::beta_binomial() instead of custom family beta_binomial2 (c6c78fb7).
compare_* functions now have N(S)EC as default behaviour (c4c84ba1).
Changed argument name precision to resolution in many functions to maintain syntax compatibility with brms (727d6700).
Standardised plot style between sample_priors and check_priors (6c59af07).

Improved speed in test runs for CRAN (d5d097fb).
Aligned generic method consistency for rhat (afb10577).
Fixed a bug relating to 01 bounded x data in define_prior (3ab93e0).
Fixed messages returned for set_distirbution (f483160).
Reduced n_trials and deleted unnecessary set.seed in while call for make_good_inits (3c5f084).

Fixed bug introduced when implementing recycling the seed passed to bnec (01394a17).
Included additional criteria in the initial values algorithm to ensure initial values can be fit in stan (fe89484a).

Cleaned parameter title names in sample_priors (6973bae1).
Small tweak to initialisation search, such that the seed used for a bnec call (via ... arguments to brms::brm) gets recycled and therefore it generates the same initialisation values across platforms (c74a3c46).

Many improvements to package following suggestions from JSS editors. These include many things like dependency on R 4.1 to support native pipeOp, revamp of predict method for classes, major overhaul on package documentation, and much more. All issues were dealt with collectively via a milestone.

Fixed issue with gsub substitution of x in original brms non-linear formulas, and added various tests (fa588fb).

Addition of herbicide data (2b13ef5).
streamlined check_* functions for negative predictors vectors – no error anymore (via check_data), now drop models with informative message (via check_models) (f134311).

bnec now works exclusively with formulas (4bccc07, d3531b4, bccb0da, 340269e).
Added +, c and update methods via a common class bnecfit (d5e81ab, 3adf3fa).
Fixes to ecx, nec and nsec following new formula-based implementation (6ec1372, 0a9d307 and 19a37b9).
Fixes to predict methods following formula-based implementation (8843a1c, 08484a7).
Dispersion now takes a bayesnecfit as input (200bc11).

Added brms::bernoulli to the list of allowed model distributions (7606461).
Made identity the default link (6640867).
Added more controls and tweaks to checking model relative to input data (85a3819), 065a445).
Added formula and model.frame methods to main classes (9df4a64).
Upgraded ggbnec to autoplot as bayesnec standard ggplot2 plotting method (65fe15f).
Enhanced handling of argument loo_controls in bnec to allow argument for both brms::add_criterion and loo::loo_model_weights (9712fcc).
Added Bayesian R² to summary (9a71a3c).
Expanded bnec’s capacity to accept input x and y vectors, data frames (f256b39) and formulas (32e74ac).
Corrected error for logit link cases for the beta_binomial2 where data contain 0 and 1 to ensure appropriate prior values on top and bot (4158237).
Series of internal fixes to standardise function class outputs (81369bb, 1c70efe, 5bce2b5, 455ca70, 5e6b41e).

If link functions are not specified in bnec, then the default link function is used; previous versions of bayesnec used the identity link.
An additional family has been added betabinomial2 for over dispersered binomial data.
The package supports using link functions for generalized modelling, which appears to be more stable and is also in line with more typical generalised modelling approaches.
There are multiple options for model weights calculation from the loo package. The default is “pseudobma BB”.
There is now a compare_posterior function that also includes a bootstrapping procedure. This can be used to compare model fits across different datasets, or even different model sets for the same dataset (ie nec v ecx models). Please see the vignette for examples of usage.
There is a vignette detailing the models available in bayesnec. Note that not all models are suitable for all families, and also depending if link functions are used.
A new check_chains function has been added to allow chain plotting in base R and that works more smoothly with plotting chains for multiple fits for bayesmanec objects.

bayesnec 2.1.2.0