Local proper scoring rules of order two

By W. Ehm, Tilmann Gneiting. 2011

46 citations recorded by the source corpus.

Scoring rules assess the quality of probabilistic forecasts, by assigning a numerical score based on the predictive distribution and on the event or value that materializes. A scoring rule is proper if it encourages truthful reporting. It is local of order $k$ if the score depends on the predictive density only through its value and the values of its derivatives of order up to $k$ at the realizing event. Complementing fundamental recent work by Parry, Dawid and Lauritzen, we characterize the local proper scoring rules of order 2 relative to a broad class of Lebesgue densities on the real line, using a different approach. In a data example, we use local and nonlocal proper scoring rules to assess statistically postprocessed ensemble weather forecasts.

Subfields: Atmospheric Science, Finance, Global and Planetary Change

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Atmospheric Science

1. Matthew Parry
2. A. P. Dawid
3. Steffen L. Lauritzen

In Finance

1. Matthew Parry
2. A. P. Dawid
3. Steffen L. Lauritzen

In Global and Planetary Change

1. Matthew Parry
2. A. P. Dawid
3. Steffen L. Lauritzen

Citations in the corpus

• Proper local scoring rules (2011, methodology): “In a companion paper to this one, Ehm and Gneiting (2012) conduct a deep investigation of order 2 proper local rules, using an elegant construction complementary to ours.”