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… scaled Year to avoid minor snapshot changes in future
… samples 0 iterations. Other than having an empty sample array, the mcmc object dimensions and returned bboufit object remain identical
3 tasks
nimble 1.4.0 moved Laplace approximation to the nimbleQuad package. The deprecated stubs in nimble fail with "attempt to set an attribute on NULL" during compileNimble. Additionally, nimbleQuad returns generic parameter names (param_trans_1, re_trans_1) on the transformed scale. Fix by: - Adding nimbleQuad to Depends so it is attached on load - Using nimbleQuad::buildLaplace via getExportedValue - Compiling the Laplace object in globalenv context so nimbleQuad internals (e.g. drop_algorithm) are found by the nimble compiler - Patching transformed-scale summary names from the original-scale summary which still returns proper parameter names Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
… bYear param (even if 0)
…ed, only added PopulationName to data.frame output and changed term naming convention (matrix to allow also vary population name)
…aribouyear x-axis labels
…formative error when fit model with niters = 0
…d functions, add bbouNationalPriors to imports
…sage to user indicating this
…require additional if block around entire model to test that observations exist or not)
… attribute at model fit time to then be retrieved.
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Extensions to bboutools - integrating changes made in https://github.com/LandSciTech/bboutoolsMultiPop and other requested changes from ECCC
In order of commits:
niters = 0inbb_fit_survival/recruitment(), which bypasses MCMC sampling but otherwise outputs the same returned object (including model, empty samples array etc.) - extensions - allow fit_ function to return model and data without MCMC sampling #85bb_predict_x_samples()equivalent to allbb_predict_x()functions to return samples instead of coefficient table. Added tests for each new samples function - extensions - ability to return samples from predict functions #83With multi-population implementation, some outputs will appear different and this change is applied across the board whether it is single or multi-population.

If a user has scripts running previous bboutools functions on single populations, these functions will still run without failure (i.e., plotting, coef, predictions, etc.). Only issues arise if customized code was developed that: