gdpar
0.1.0General Dynamic Parameter Models via Reference Anchoring
Overview
Implements a unified predictive framework in which individual parameters are decomposed as theta_i equal to theta_ref plus Delta(x_i, theta_ref), with theta_ref a population reference and Delta an explicit deviation function. The decomposition follows the Additive-Multiplicative-Modulated canonical form and is estimated through three complementary paths: hierarchical Bayesian inference via 'Stan', varying-coefficient models via penalized splines, and amortized inference via hypernetworks in 'torch'. The package provides identifiability diagnostics, validity tests for the population reference, and benchmarks against canonical zero-inflated count datasets and avian abundance data from the eBird Status and Trends project. The framework and its estimation paths are described in Gomez Julian (2026) doi:10.5281/zenodo.21046269.
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- OK2026-07-165 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
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1 release. R releases are shown for context.
- 0.1.0Latest2026-07-16 · current release
- RR 4.6.0 released · 2026-04-24
Package metadata
- First published
- 2026-07-16
- Total releases
- 1 / 1 yrs
- License
- GPL (>= 3) OSI
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