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BayesianDEB 0.2.1

Second-round JSS revision: diagnostics display polish, fully runnable (toolchain-gated) examples, and replication / manuscript reproducibility fixes.

• print.bdeb_diagnostics() now prints a compact table by default, hiding the per-time-point latent states (x_sol[i,j], L_hat[i]); the new full = TRUE argument restores the complete table (also available via summary(x)$table).
• plot.bdeb_diagnostics() likewise hides the per-time-point latent states by default for a shorter, more readable R-hat / ESS plot; the new full = TRUE argument plots every monitored quantity. The subtitle notes how many latent rows were hidden.
• bdeb_diagnose() and the bdeb_diagnostics print/summary/plot methods, plus bdeb_loo(), bdeb_derived() and bdeb_summary(), moved their examples from \dontrun{} to a cmdstanr-gated \donttest{} block, so example() runs them when a CmdStan toolchain is available (mirroring bdeb_fit()).
• plot_dose_response() now draws posterior-median EC50 (dashed red) and NEC (dotted green) reference lines, drops non-finite draws, and clips the view with coord_cartesian() so degenerate draws no longer appear as vertical artefacts.
• Replication material: a single-command replicate_all.R reproduces every manuscript figure, table and printed number in ~1 min from cached draws; every manuscript code listing is now executed and printed; outputs use a fixed seed for bit-identical reproduction; and the README maps every figure to the script that produces it.

BayesianDEB 0.2.0

JSS revision release. Comprehensive S3 class system overhaul, expanded methods coverage, and reproducible replication package.

Breaking changes

• bdeb_diagnose() now returns a bdeb_diagnostics S3 object. All output goes through print(), summary(), and plot() (type = "rhat" or "ess"). Direct list access still works (n_divergent, summary, …).
• bdeb_summary() is deprecated; use summary(fit) on a bdeb_fit object instead. The wrapper still works but emits a deprecation warning and will be removed in a future release.

New methods

• bdeb_data: print(), summary(), plot().
• bdeb_model: print(), summary(), plot().
• bdeb_prior: print(), summary(), plot().
• bdeb_prediction: print(), summary() (the latter returns a tidy time / lower / median / upper data frame).
• bdeb_diagnostics: print(), summary(), plot().
• bdeb_fit (additional lm-style methods): summary() (now the primary posterior-summary API, accepts pars and prob), confint() (posterior credible intervals), fitted() (posterior median/mean of ), residuals() (observed minus fitted), nobs() (observation count), vcov() (posterior covariance of model parameters), and logLik() (log-pointwise predictive density, lppd). fitted(), residuals(), and logLik() are available for "individual" and "growth_repro" models only.
• bdeb_derived() is now an S3 generic with a bdeb_fit method (bdeb_derived.bdeb_fit). Existing calls are unchanged; the dispatch enables future support for derived quantities on prior-only or simulated objects.

Bug fixes

• bdeb_diagnose() no longer fails on real-data fits whose generated quantities (log_lik, L_rep) contain NaN draws from sporadic ODE-solver failures. The summarise_draws() quantile lambdas now pass na.rm = TRUE.
• plot() on a bdeb_fit (type = "trace", "posterior", "pairs") now subsets draws to the requested parameters before delegating to bayesplot. Without this, NaN draws in unrelated generated quantities caused bayesplot::prepare_mcmc_array() to abort with "NAs not allowed in 'x'".

Stan

• Increased ode_bdf_tol max_num_steps from 1e4 to 1e5 in all four Stan models to reduce CVode mxstep messages during warmup.

Vignettes

• Conditional execution via requireNamespace("cmdstanr").
• Fixed plot(fit, type = "pairs") returning NULL.

Replication material

• Reorganised JSS replication material into a single zip with README, data/, outputs/, and lite/full execution modes.
• Bundled curves.txt locally to remove external dependency.

BayesianDEB 0.1.4

CRAN-review compliance release. Addresses reviewer feedback on the use of T as an identifier, which can shadow R’s built-in T symbol (= TRUE).

Breaking changes

• arrhenius(): first argument renamed from T to temp. Positional calls are unaffected (arrhenius(298.15)). Code that passed the argument by name (arrhenius(T = 298.15)) must be updated to arrhenius(temp = 298.15).
• bdeb_model(temperature = ...): the list field T was renamed to T_obs to match the Stan data naming and to remove the T shadow. Replace list(T = 298.15, T_ref = ..., T_A = ...) with list(T_obs = 298.15, T_ref = ..., T_A = ...).

CRAN compliance

• bdeb_diagnose() and bdeb_ec50() now expose a verbose = TRUE argument. All user-facing output (diagnostic alerts and summary tables) is routed through cli / [message()] rather than direct print() calls, so it can be silenced with [suppressMessages()] or by passing verbose = FALSE. Return values are unchanged.

Documentation

• Updated R/utils.R, R/data_prep.R, R/model_spec.R and man/arrhenius.Rd, man/bdeb_model.Rd, man/temperature_to_stan_data.Rd, man/build_stan_data_individual.Rd to reflect the renaming.
• Case-study vignette updated to use arrhenius(temp = ...).
• Tests updated for the new temperature$T_obs field.
• \dontrun{} replaced with runnable examples for prior_species(), bdeb_tox() and bdeb_prior_predictive() (all execute in < 0.2 s against bundled datasets). bdeb_fit() retains \dontrun{} because it requires the external CmdStan toolchain and a single Stan compilation + MCMC run takes > 30 seconds; the Rd comment explains the reason.

Citation

• Switched README badge and CITATION.cff from the version-specific DOI (10.5281/zenodo.19500753, v0.1.3) to the concept DOI (10.5281/zenodo.19443804), which always resolves to the latest archived version. The v0.1.4 version DOI is 10.5281/zenodo.19642839 for anyone needing to cite this specific release.

BayesianDEB 0.1.3

New features and data release.

New features

• prior_species(): species-specific priors from the AmP collection for E. fetida, E. andrei, F. candida, D. magna, and L. rubellus.
• plot(fit, type = "prior_posterior"): prior vs. posterior density comparison plot.

New datasets

• eisenia_neuhauser: real E. fetida growth data from Neuhauser, Hartenstein & Kaplan (1980), 37 group-mean measurements over 250 days.
• eisenia_cd: real Eisenia andrei cadmium toxicity data from Van Gestel et al. (1991), 5 concentration groups over 85 days.

Documentation

• Updated DOI to Zenodo 10.5281/zenodo.19500753.

BayesianDEB 0.1.2

ODE solver upgrade and bug fix release.

Breaking changes

• R-side ODE integration now uses deSolve::lsoda() (adaptive BDF/Adams) instead of fixed-step Euler. This matches the BDF solver used in Stan, ensuring numerical consistency between R-side simulation and Stan-side inference. The dt parameter now controls output resolution, not integration accuracy.
• deSolve (>= 1.40) added to Imports.

Bug fixes

• Fixed bdeb_ec50()$NEC returning a data frame instead of numeric draws — median(ec50$NEC) now works correctly.
• Fixed build_stan_data_hierarchical() crashing when growth data starts at time = 0 (same fix as individual model in 0.1.1).
• Fixed build_stan_data_debtox() crashing when growth or reproduction data starts at time = 0.
• Fixed build_stan_data_growth_repro() t=0 handling producing NA index matches — replaced convoluted fix with consistent epsilon shift across growth and reproduction times.

Internal

• Renamed internal helpers sim_deb_euler() / sim_debtox_euler() to sim_deb_lsoda() / sim_debtox_lsoda() to reflect solver.
• Updated package documentation to describe LSODA solver instead of Euler.

BayesianDEB 0.1.1

Bug fix and hardening release.

Bug fixes

• Fixed ode_bdf_tol crash when growth data starts at time = 0: replaced with 1e-3 epsilon since Stan requires t_obs > t0.
• Fixed %||% operator not imported: replaced with explicit if (is.null(...)) in bdeb_predict().
• Fixed silent rnorm() fallback for unknown prior families in bdeb_prior_predictive(): now throws informative error.
• Fixed bdeb_predict(newdata = NULL) using t_obs instead of t_L for "growth_repro" models.
• Fixed bdeb_predict() silently returning raw draws when L_hat is missing: now throws informative error.
• Fixed DEBtox reproduction using cumulative R instead of interval delta_R = k_R * (R(t_end) - R(t_start)): now consistent with growth_repro model.
• Fixed phi_R prior hardcoded in DEBtox Stan model: now uses prior_phi_R_mu/sd from R prior system.
• Fixed deb_fluxes() computing p_G with redundant / E_G * E_G.
• Fixed growth_rate formula: was v/3 * p_M/(kappa*E_G), now correct Kooijman Eq. 3.23: k_M * g / (3*(f+g)).

Safety improvements

• "individual" and "growth_repro" models now hard-error (not warn) when data contains multiple individuals.
• DEBtox auto-aggregates multi-individual concentration groups to means with explicit warning.
• Removed survival argument from bdeb_data() (was accepted but not implemented — “feature mirage”).
• All prior constructors validate hyperparameters (sigma > 0, a > 0, rate > 0, nu > 1).
• bdeb_data() validates f_food in [0, 1].
• bdeb_fit() validates all sampling parameters (chains, iterations, adapt_delta, max_treedepth, threads).
• arrhenius() validates T > 0, T_ref > 0, T_A >= 0.
• bdeb_model() validates prior objects, observation objects, and temperature fields (must be positive finite scalars).
• bdeb_fit() wraps Stan compilation and sampling in tryCatch with contextualised error messages.
• repro_to_intervals() warns when dropping individuals with < 2 observations.
• validate_growth() warns when max length > 10 cm (possibly physical rather than structural length).
• DEBtox reproduction time matching now uses strict match() instead of nearest-neighbour which.min().

New features

• bdeb_loo(): LOO cross-validation via loo::loo() with endpoint argument for "growth_repro" models.
• bdeb_prior_predictive(): R-side prior predictive simulation with print() and plot() methods.
• bdeb_session_info(): reproducibility report (R, Stan, package versions, fit configuration, Stan model hash).
• coef.bdeb_fit(): S3 method returning posterior medians or means.
• deb_simulate(), debtox_simulate(): standalone DEB/DEBtox simulators, independent of Stan.
• L_m added to bdeb_derived(): maximum structural length at f=1.
• plot.bdeb_prediction(): S3 plot method for prediction objects.
• Observation model switching now fully implemented in all 4 Stan models via integer flags (no recompilation needed).
• Arrhenius temperature correction implemented in all 4 Stan models.
• Within-chain parallelism via reduce_sum for hierarchical and DEBtox models.
• threads_per_chain argument in bdeb_fit().
• seed argument in bdeb_predict(), plot_dose_response(), and plot(fit, type = "trajectory").
• dt and t_end arguments in plot_dose_response().
• Reproducibility metadata (seed, versions, timestamp) stored in bdeb_fit object.
• inst/CITATION with package and Kooijman (2010) entries.
• CITATION.cff with Zenodo DOI.

Documentation

• Structural vs physical length documented throughout (delta_M).
• All derived quantity formulas reference Kooijman (2010) equations.
• Prior calibration rationale documented with AmP ranges.
• Feature status table in README with stable/beta/planned.
• “Current limitations” section in README.
• “Numerical layers” section in package docs (Stan exact vs R-side approximate).
• Lifecycle annotations on all functions and models.

Tests

• 901 tests across 16 files (up from 58).
• New test categories: API contracts, scientific consistency, snapshot/regression, deep validation, end-to-end integration.

BayesianDEB 0.1.0

Initial release.

Models

• Individual-level growth model (2-state DEB: reserve, structure).
• Growth + reproduction model (3-state DEB: reserve, structure, reproduction buffer) with negative binomial observation model.
• Hierarchical multi-individual growth model with non-centred parameterisation and partial pooling of assimilation rates.
• DEBtox (TKTD) model for ecotoxicology with scaled internal damage, stress on assimilation, and analytical EC50/NEC computation.

Features

• Declarative model specification via bdeb_model().
• Prior specification functions for all standard DEB parameters: prior_lognormal(), prior_beta(), prior_halfnormal(), and others.
• Sensible weakly informative default priors via prior_default(), calibrated against the AmP collection (Marques et al., 2018).
• Observation model selection: obs_normal(), obs_lognormal(), obs_student_t(), obs_poisson(), obs_negbinom().
• MCMC fitting via cmdstanr with bdeb_fit().
• Convergence diagnostics: bdeb_diagnose() reports R-hat, ESS, divergences, and E-BFMI (Vehtari et al., 2021).
• Posterior predictive checks with bdeb_ppc().
• Derived quantity computation: bdeb_derived() for ultimate length, von Bertalanffy growth rate, and somatic maintenance rate constant.
• Publication-quality plots: trace, posterior density, pairs, trajectory, and PPC overlays.
• DEBtox helpers: bdeb_tox(), bdeb_ec50(), plot_dose_response().
• Utility functions: arrhenius() temperature correction, deb_fluxes() energy flux calculator, repro_to_intervals() data converter.

Data

• eisenia_growth: simulated Eisenia fetida growth (21 individuals, 12 weeks).
• folsomia_repro: simulated Folsomia candida reproduction test (5 Cd concentrations, 6 replicates).
• debtox_growth: simulated growth under toxicant exposure (4 concentrations, 10 individuals each, 6 weeks).

Vignettes

• getting_started: overview of the package workflow.
• case_study_eisenia_folsomia: full workflow with Eisenia growth (individual + hierarchical) and Folsomia DEBtox analysis.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.