CausalMixGPD
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    • Start Hub
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    • Reference hub
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On this page

  • Unconditional (bulk-only)
  • Unconditional (bulk + GPD tail)
  • Conditional (bulk-only)
  • Conditional (bulk + GPD tail)
  • Causal
  • Clustering
  • Other resources
  • Prereqs
  • Outputs
  • Interpretation
  • Next

Examples

Task-oriented templates organized by analysis type

This page indexes the example templates. Each link below points to a single runnable page that shows a complete workflow: data setup → fit → diagnostics → prediction/interpretation.

Use examples as templates: copy the minimal pattern (bundle/fit + S3 methods) and then swap kernels/backends/tail settings as your problem demands.

Note

If you are new, start with the Start hub and then return here. The full API documentation lives in pkgdown.

Unconditional (bulk-only)

  • ex01 — Unconditional DPM (CRP)
  • ex02 — Unconditional DPM (SB)

Unconditional (bulk + GPD tail)

  • ex03 — Unconditional DPM+GPD (CRP)
  • ex04 — Unconditional DPM+GPD (SB)

Conditional (bulk-only)

  • ex05 — Conditional DPM (CRP)
  • ex06 — Conditional DPM (SB)

Conditional (bulk + GPD tail)

  • ex07 — Conditional DPM+GPD (CRP)
  • ex08 — Conditional DPM+GPD (SB)

Causal

  • ex09 — Causal, no X (CRP)
  • ex10 — Causal, X no PS (SB)
  • ex11 — Causal, same backend (CRP)
  • ex12 — Causal, same backend (SB)
  • ex13 — Causal, different backends (CRP)
  • ex14 — Causal, different backends (SB)

Clustering

  • ex15 — Clustering with GPD tail, weights + covariates
  • ex16 — Clustering with regular kernel, parameter links + covariates

Other resources

  • Start hub: Start
  • Website roadmap: Roadmaps
  • Advanced hub: Advanced
  • Kernels hub: Kernels
  • API reference (pkgdown): Reference

Prereqs

  • Required packages and data for this page are listed in the setup chunks above.

Outputs

  • This page renders model fits, diagnostics, and summary artifacts generated by package APIs.

Interpretation

  • Canonical concept page: Model Umbrella
  • Treat this page as an application/example view and use the canonical page for core definitions.

Next

  • Continue to the linked canonical concept page, then return for implementation-specific details.
(c) CausalMixGPD - Bayesian semiparametric modeling for heavy-tailed data
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