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spDBL 1.1.1

• Calibration accepts a positive-definite discrepancy covariance scale U with non-unit diagonal, preserving the original research experiment’s discrepancy-to-observation variance ratio.

• Default emulator coefficient sampling to smoothed marginals conditional on a shared covariance draw. Add sampling = “joint” for coherent backward paths under both scalar-variance and inverse-Wishart covariance models.

• Let calibration preparation inherit or explicitly change the fitted sampling method, with sampling metadata retained in saved objects and fit summaries.

• Default calibration to one chain, one iteration, zero warmup, and one retained sample per emulator draw. Longer iterations and other controls remain options; warmup, retained-sample counts, and default controls adapt to the settings.

• Default the installed reproduction script to the marginal oneiter500 profile; update the vignettes and recorded example to these defaults.

spDBL 1.1.0

• Add optional RStan calibration with Gaussian discrepancy marginalization, coherent posterior recovery, equal pooling of emulator conditionals, and conditional-fit diagnostics.
• Add a sigma2R option and complete metadata to the emulator wrapper.
• Add an offline GP for predicting AR design rows without further PDE solves. Its interpolation uncertainty remains excluded from calibration.
• Extend exact FFBS prediction with fixed coefficient trajectories, cached factors, and conditional covariance; preserve the default mean interface.
• Correct sigma2R trajectory sampling to condition backward on sampled states.
• Add compact calibration data, two package vignettes, and installed reproduction scripts. One-iteration runs are labeled execution experiments.
• Show 500 one-transition calibration samples in the end-to-end vignette, with eta histograms and a variance/discrepancy/field comparison panel.

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.
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