New Features

• Support the Cox proportional hazards model for time-to-event data via family cox. (#230, #962)
• Support method loo_moment_match, which can be used to update a loo object when Pareto k estimates are large.

Other Changes

• Improve the prediction behavior in post-processing methods when sampling new levels of grouping factors via sample_new_levels = "uncertainty". (#956)

Bug Fixes

• Fix minor problems with MKL on CRAN.

brms 2.13.3

New Features

• Fix shape parameters across multiple monotonic terms via argument id in function mo to ensure conditionally monotonic effects. (#924)
• Support package rtdists as additional backend of wiener distribution functions thanks to the help of Henrik Singmann. (#385)

Bug Fixes

• Fix generated Stan Code of models with improper global priors and constant priors on some coefficients thanks to Frank Weber. (#919)
• Fix a bug in conditional_effects occuring for categorical models with matrix predictors thanks to Jamie Cranston. (#933)

Other Changes

• Adjust behavior of the rate addition term so that it also affects the shape parameter in negbinomial models thanks to Edward Abraham. (#915)
• Adjust the default inverse-gamma prior on length-scale parameters of Gaussian processes to be less extreme in edge cases thanks to Topi Paananen.

New Features

• Constrain ordinal thresholds to sum to zero via argument threshold in ordinal family functions thanks to the help of Marta Kołczyńska.
• Support posterior_linpred as method in conditional_effects.
• Use std_normal in the Stan code for improved efficiency.
• Add arguments cor, id, and cov to the functions gr and mm for easy specification of group-level correlation structures.
• Improve workflow to feed back brms-created models which were fitted somewhere else back into brms. (#745)
• Improve argument int_conditions in conditional_effects to work for all predictors not just interactions.
• Support multiple imputation of data passed via data2 in brm_multiple. (#886)
• Fully support the emmeans package thanks to the help of Russell V. Lenth. (#418)
• Control the within-block position of Stan code added via stanvar using the position argument.

Bug Fixes

• Fix issue in Stan code of models with multiple me terms thanks to Chris Chatham. (#855, #856)
• Fix scaling problems in the estimation of ordinal models with multiple threshold vectors thanks to Marta Kołczyńska and Rok Češnovar.
• Allow usage of std_normal in set_prior thanks to Ben Goodrich. (#867)
• Fix Stan code of distributional models with weibull, frechet, or inverse.gaussian families thanks to Brian Huey and Jack Caster. (#879)
• Fix Stan code of models which are truncated and weighted at the same time thanks to Michael Thompson. (#884)
• Fix Stan code of multivariate models with custom families and data variables passed to the likelihood thanks to Raoul Wolf. (#906)

Other Changes

• Reduce minimal scale of several default priors from 10 to 2.5. The resulting priors should remain weakly informative.
• Automatically group observations in gp for increased efficiency.
• Rename parse_bf to brmsterms and deprecate the former function.
• Rename extract_draws to prepare_predictions and deprecate the former function.
• Deprecate using a model-dependent rescor default.
• Deprecate argument cov_ranef in brm and related functions.
• Improve several internal interfaces. This should not have any user-visible changes.
• Simplify the parameterization of the horseshoe prior thanks to Aki Vehtari. (#873)
• Store fixed distributional parameters as regular draws so that they behave as if they were estimated in post-processing methods.

New Features

• Fix parameters to constants via the prior argument. (#783)
• Specify autocorrelation terms directly in the model formula. (#708)
• Translate integer covariates in non-linear formulas to integer arrays in Stan.
• Estimate sigma in combination with fixed correlation matrices via autocorrelation term fcor.
• Use argument data2 in brm and related functions to pass data objects which cannot be passed via data. The usage of data2 will be extended in future versions.
• Compute pointwise log-likelihood values via log_lik for non-factorizable Student-t models. (#705)

Bug Fixes

• Fix output of posterior_predict for multinomial models thanks to Ivan Ukhov.
• Fix selection of group-level terms via re_formula in multivariate models thanks to Maxime Dahirel. (#834)
• Enforce correct ordering of terms in re_formula thanks to @ferberkl. (#844)
• Fix post-processing of multivariate multilevel models when multiple IDs are used for the same grouping factor thanks to @lott999. (#835)
• Store response category names of ordinal models in the output of posterior_predict again thanks to Mattew Kay. (#838)
• Handle NA values more consistently in posterior_table thanks to Anna Hake. (#845)
• Fix a bug in the Stan code of models with multiple monotonic varying effects across different groups thanks to Julian Quandt.

Other Changes

• Rename offset variables to offsets in the generated Stan code as the former will be reserved in the new stanc3 compiler.

Bug Fixes

• Fix version requirement of the loo package.
• Fix effective sample size note in the summary output. (#824)
• Fix an edge case in the handling of covariates in special terms thanks to Andrew Milne. (#823)
• Allow restructuring objects multiple times with different brms versions thanks to Jonathan A. Nations. (#828)
• Fix validation of ordered factors in newdata thanks to Andrew Milne. (#830)

New Features

• Support grouped ordinal threshold vectors via addition argument resp_thres. (#675)
• Support method loo_subsample for performing approximate leave-one-out cross-validation for large data.
• Allow storing more model fit critera via add_criterion. (#793)

Bug Fixes

• Fix prediction uncertainties of new group levels for sample_new_levels = "uncertainty" thanks to Dominic Magirr. (#779)
• Fix problems when using pp_check on censored models thanks to Andrew Milne. (#744)
• Fix error in the generated Stan code of multivariate zero_inflated_binomial models thanks to Raoul Wolf. (#756)
• Fix predictions of spline models when using addition argument subset thanks to Ruben Arslan.
• Fix out-of-sample predictions of AR models when predicting more than one step ahead.
• Fix problems when using reloo or kfold with CAR models.
• Fix problems when using fitted(..., scale = "linear") with multinomial models thanks to Santiago Olivella. (#770)
• Fix problems in the as.mcmc method for thinned models thanks to @hoxo-m. (#811)
• Fix problems in parsing covariates of special effects terms thanks to Riccardo Fusaroli (#813)

Other Changes

• Rename marginal_effects to conditional_effects and marginal_smooths to conditional_smooths. (#735)
• Rename stanplot to mcmc_plot.
• Add method pp_expect as an alias of fitted. (#644)
• Model fit criteria computed via add_criterion are now stored in the brmsfit$criteria slot.
• Deprecate resp_cat in favor of resp_thres.
• Deprecate specifying global priors on regression coefficients in categorical and multivariate models.
• Improve names of weighting methods in model_weights.
• Deprecate reserved variable intercept in favor of Intercept.
• Deprecate argument exact_match in favor of fixed.
• Deprecate functions add_loo and add_waic in favor of add_criterion.

New Features

• Improve convergence diagnostics in the summary output. (#712)
• Use primitive Stan GLM functions whenever possible. (#703)
• Pass real and integer data vectors to custom families via the addition arguments vreal and vint. (#707)
• Model compound symmetry correlations via cor_cosy. (#403)
• Predict sigma in combination with several autocorrelation structures. (#403)
• Use addition term rate to conveniently handle denominators of rate responses in log-linear models.
• Fit BYM2 CAR models via cor_car thanks to the case study and help of Mitzi Morris.

Other Changes

• Substantially improve the sampling efficiency of SAR models thanks to the GitHub user aslez. (#680)
• No longer allow changing the boundaries of autocorrelation parameters.
• Set the number of trials to 1 by default in marginal_effects if not specified otherwise. (#718)
• Use non-standard evaluation for addition terms.
• Name temporary intercept parameters more consistently in the Stan code.

Bug Fixes

• Fix problems in the post-processing of me terms with grouping factors thanks to the GitHub user tatters. (#706)
• Allow grouping variables to start with a dot thanks to Bruno Nicenboim. (#679)
• Allow the horseshoe prior in categorical and related models thanks to the Github user tatters. (#678)
• Fix extraction of prior samples for overall intercepts in prior_samples thanks to Jonas Kristoffer Lindelov. (#696)
• Allow underscores to be used in category names of categorical responses thanks to Emmanuel Charpentier. (#672)
• Fix Stan code of multivariate models with multi-membership terms thanks to the Stan discourse user Pia.
• Improve checks for non-standard variable names thanks to Ryan Holbrook. (#721)
• Fix problems when plotting facetted spaghetti plots via marginal_smooths thanks to Gavin Simpson. (#740)

New Features

• Specify non-linear ordinal models. (#623)
• Allow to fix thresholds in ordinal mixture models (#626)
• Use the softplus link function in various families. (#622)
• Use QR decomposition of design matrices via argument decomp of brmsformula thanks to the help of Ben Goodrich. (#640)
• Define argument sparse separately for each model formula.
• Allow using bayes_R2 and loo_R2 with ordinal models. (#639)
• Support cor_arma in non-normal models. (#648)

Other Changes

• Change the parameterization of monotonic effects to improve their interpretability. (#578)
• No longer support the cor_arr and cor_bsts correlation structures after a year of deprecation.
• Refactor internal evaluation of special predictor terms.
• Improve penality of splines thanks to Ben Goodrich and Ruben Arslan.

Bug Fixes

• Fix a problem when applying marginal_effects to measurement error models thanks to Jonathan A. Nations. (#636)
• Fix computation of log-likelihood values for weighted mixture models.
• Fix computation of fitted values for truncated lognormal and weibull models.
• Fix checking of response boundaries for models with missing values thanks to Lucas Deschamps.
• Fix Stan code of multivariate models with both residual correlations and missing value terms thanks to Solomon Kurz.
• Fix problems with interactions of special terms when extracting variable names in marginal_effects.
• Allow compiling a model in brm_multiple without sampling thanks to Will Petry. (#671)

New Features

• Fit multinomial models via family multinomial. (#463)
• Fit Dirichlet models via family dirichlet. (#463)
• Fit conditional logistic models using the categorical and multinomial families together with non-linear formula syntax. (#560)
• Choose the reference category of categorical and related families via argument refcat of the corresponding family functions.
• Use different subsets of the data in different univariate parts of a multivariate model via addition argument subset. (#360)
• Control the centering of population-level design matrices via argument center of brmsformula and related functions.
• Add an update method for brmsfit_multiple objects. (#615)
• Split folds after group in the kfold method. (#619)

Other changes

• Deprecate compare_ic and instead recommend loo_compare for the comparison of loo objects to ensure consistency between packages. (#414)
• Use the glue package in the Stan code generation. (#549)
• Introduce mvbind to eventually replace cbind in the formula syntax of multivariate models.
• Validate several sampling-related arguments in brm before compiling the Stan model. (#576)
• Show evaluated vignettes on CRAN again. (#591)
• Export function get_y which is used to extract response values from brmsfit objects.

Bug fixes

• Fix an error when trying to change argument re_formula in bayes_R2 thanks to the GitHub user emieldl. (#592)
• Fix occasional problems when running chains in parallel via the future package thanks to Jared Knowles. (#579)
• Ensure correct ordering of response categories in ordinal models thanks to Jonas Kristoffer Lindelov. (#580)
• Ignore argument resp of marginal_effects in univariate models thanks to Vassilis Kehayas. (#589)
• Correctly disable cell-mean coding in varying effects.
• Allow to fix parameter ndt in drift diffusion models.
• Fix Stan code for t-distributed varying effects thanks to Ozgur Asar.
• Fix an error in the post-processing of monotonic effects occuring for multivariate models thanks to James Rae. (#598)
• Fix lower bounds in truncated discrete models.
• Fix checks of the original data in kfold thanks to the GitHub user gcolitti. (#602)
• Fix an error when applying the VarCorr method to meta-analytic models thanks to Michael Scharkow. (#616)

New features

• Fit approximate and non-isotropic Gaussian processes via gp. (#540)
• Enable parallelization of model fitting in brm_multiple via the future package. (#364)
• Perform posterior predictions based on k-fold cross-validation via kfold_predict. (#468)
• Indicate observations for out-of-sample predictions in ARMA models via argument oos of extract_draws. (#539)

Other changes

• Allow factor-like variables in smooth terms. (#562)
• Make plotting of marginal_effects more robust to the usage of non-standard variable names.
• Deactivate certain data validity checks when using custom families.
• Improve efficiency of adjacent category models.
• No longer print informational messages from the Stan parser.

Bug fixes

• Fix an issue that could result in a substantial efficiency drop of various post-processing methods for larger models.
• Fix an issue when that resulted in an error when using fitted(..., scale = "linear") with ordinal models thanks to Andrew Milne. (#557)
• Allow setting priors on the overall intercept in sparse models.
• Allow sampling from models with only a single observation that also contain an offset thanks to Antonio Vargas. (#545)
• Fix an error when sampling from priors in mixture models thanks to Jacki Buros Novik. (#542)
• Fix a problem when trying to sample from priors of parameter transformations.
• Allow using marginal_smooths with ordinal models thanks to Andrew Milne. (#570)
• Fix an error in the post-processing of me terms thanks to the GitHub user hlluik. (#571)
• Correctly update warmup samples when using update.brmsfit.