Vignettes and other documentation
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Vignettes from package 'gdpar'
| gdpar::v00_framework_overview | Predictive Models with Dynamic Individual Parameters: A Unifying Conceptual Framework | HTML | source | R code | |
| gdpar::v01_amm_identifiability | The AMM Canonical Form and Identifiability Conditions | HTML | source | R code | |
| gdpar::v02_gnoseological_validity | Gnoseological Validity Conditions for the Population Reference | HTML | source | R code | |
| gdpar::v03_special_cases | Standard Predictive Models as Formal Special Cases of the AMM | HTML | source | R code | |
| gdpar::v04_asymptotics_path1_bayesian | Asymptotic Theory for Path 1 (Hierarchical Bayesian) | HTML | source | R code | |
| gdpar::v05_asymptotics_path2_vcm | Asymptotic Theory for Path 2 (Varying-Coefficient via Penalized Splines) | HTML | source | R code | |
| gdpar::v06_asymptotics_path3_hypernetwork | Asymptotic Theory for Path 3 (Hypernetwork) | HTML | source | R code | |
| gdpar::v07_eb_vs_fb | Empirical Bayes vs. Fully Bayes Treatment of the Population Reference | HTML | source | R code | |
| gdpar::v07b_eb_multivariate | Empirical Bayes vs. Fully Bayes -- Multivariate Extension | HTML | source | R code | |
| gdpar::v08_cate_ite_positioning | Positioning AMM relative to the CATE / ITE Literature | HTML | source | R code | |
| gdpar::v08b_cate_ite_bridge_implementation | The T-learner AMM-side Causal Bridge | HTML | source | R code | |
| gdpar::v08c_meta_learner_comparison | Theoretical Addendum 8.5.B: Comparison against External Meta-learners | HTML | source | R code | |
| gdpar::v08d_amm_subphases | AMM Sub-phases 8.3.1 to 8.3.10 -- Theoretical Canonization | HTML | source | R code | |
| gdpar::v09_cognitive_motivation | Cognitive Motivation: From Driver Prediction to Reference-Anchored Individuation | HTML | source | R code | |
| gdpar::vop00_quickstart | Quickstart: A First Fit in Five Minutes | HTML | source | R code | |
| gdpar::vop01_parametrization_toggle | Parametrization Toggle: Operational Guide | HTML | source | R code | |
| gdpar::vop02_arbitrary_p | Arbitrary p: Operational Cookbook for Multivariate Fits | HTML | source | R code | |
| gdpar::vop03_grouped_anchors | Per-group hierarchical anchors: Operational Guide | HTML | source | R code | |
| gdpar::vop03_regression_testing | Regression Testing of MCMC Outputs (Experimental) | HTML | source | R code | |
| gdpar::vop04_amm_intermediate | Intermediate AMM Specifications: B-spline W Bases and Heterogeneous Families per Slot | HTML | source | R code | |
| gdpar::vop05_distributional_K_dharma | Distributional Regression K > 1 and Residual Diagnostics with DHARMa | HTML | source | R code | |
| gdpar::vop06_meta_learner_comparison | Comparing the AMM-side T-learner against External Meta-learners | HTML | source | R code | |
| gdpar::vop07_eb_workflow | The Empirical-Bayes Workflow in gdpar | HTML | source | R code | |
| gdpar::vop08_geometric_robustness | Geometric Robustness of Sampling (Block RG) | HTML | source | R code | |
| gdpar::vop09_dependence_robust | Dependence-Robust Inference in gdpar (Axis 2) | HTML | source | R code |