Strictly proper scoring rules, prediction, and estimation

Gneiting, T., & Raftery, A. E. (2007). Strictly proper scoring rules, prediction, and estimation. Journal of the American Statistical Association, 102(477), 359-378.

Type

Journal article

Intellectual base

Primary research

Year

2007

DOI

10.1198/016214506000001437

Link

https://doi.org/10.1198/016214506000001437

Cited from

statistics_experimental_design

Cited by

3 citations across 3 artifacts.

Each citation links to the sentence it supports in the citing article.

Primes

• Calibration
  • This decomposition breaks what might otherwise seem like an overwhelming problem—"make this system accurate"—into discrete, manageable steps, paralleling the way Gneiting and Raftery (2007) decompose strictly proper scoring rules into reliability and resolution components.

    This sourceModern theory of proper scoring rules on general probability spaces; rules are proper when honest probabilistic forecasts maximize expected score, supporting principled measurement of calibration (reliability) and resolution.

Domain-specific

• Forecast skill
  • The entry records a descriptive analytical identity; practical use requires the governing domain's evidence, standards, and safety obligations.
• Scoring Rule
  • Gneiting and Raftery give the general probability-space formulation and connect proper rules to entropy, divergence, estimation, and forecast comparison.

Verification

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