Kernels

Kernel Selection Hub

Choose a bulk kernel based on support, shape, and tail behavior. Then move into the catalog pages.

Kernel catalog index Summary backend table

How to choose

1. Confirm support: real-line vs positive-support.
2. Match bulk behavior: symmetry, skew, heavy tails, multimodality tolerance.
3. Decide backend workflow with Start backends and workflow.
4. Validate with examples and diagnostics.

Key kernel pages

• Normal
• Laplace
• Cauchy
• Lognormal
• Gamma
• Amoroso
• Inverse Gaussian (base)
• Inverse Gaussian (mixture)

Supporting pages

• Mathematical definitions and conventions
• Introduction with GPD kernel
• Summary distribution-backend reference

API and registries

• Kernel support table
• Kernel registry
• Tail registry

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: Introduction With Gpd Kernel
• 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.