An evaluation of tests of distributional forecasts

By Pablo Noceti, Jeremy Smith, S. Hodges. 2003

78 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/c9f5183dd58d62089157cdcf04c31b190cabce1e

How researchers see this paper

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

In Economics and Econometrics

1. Tilmann Gneiting
2. A. Jore
3. Shaun P. Vahey
4. Johannes Resin
5. Ian T. Jolliffe
6. Adrian E. Raftery
7. James Mitchell
8. Fadoua Balabdaoui

In Finance

1. Johannes Resin
2. Adrian E. Raftery
3. Tilmann Gneiting
4. James Mitchell
5. Fadoua Balabdaoui
6. Shaun P. Vahey
7. A. Jore
8. Andrew J. Patton

In Management Science and Operations Research

1. Tilmann Gneiting
2. Johannes Resin
3. A. Jore
4. Shaun P. Vahey
5. Adrian E. Raftery
6. James Mitchell
7. Fadoua Balabdaoui
8. James W. Taylor

Citations in the corpus

• Probabilistic forecasts, calibration and sharpness (2007, methodology): “Formal tests of uniformity can be employed and have been studied by Anderson (1996), Talagrand et al. (1997), Noceti et al. (2003), Garratt et al. (2003), Wallis (2003), Candille and Talagrand (2005) and Corradi and Swanson (2006), among others.”
• Nowcasting GDP in Real Time: A Density Combination Approach (2014, unknown): “Other tests of uniformity employed are the Anderson–Darling (AD) test (see Noceti, Smith, and Hodges 2003) and a Pearson chi-squared test, as suggested by Wallis (2003).”
• Combining forecast densities from VARs with uncertain instabilities (2010, methodology): “This is designed to detect forecast failure in the tails of the forecast density.7 We also consider the Anderson-Darling (AD) test for uniformity, a modification of the Kolmogorov-Smirnov test, intended to give more weight to the tails (and advocated by Noceti et al. (2003)).”
• Regression diagnostics meets forecast evaluation: conditional calibration, reliability diagrams, and coefficient of determination (2021, methodology): “…the empirical CDF of the PIT values, such as the classical Kolmogorov-Smirnov (KS) statistic, as suggested and used to test for PIT calibration by Noceti et al. (2003) and Knüppel (2015), or, more generally, tests based on distance measures between the empirical CDF of the PIT values, and the…”
• Verification tools for probabilistic forecasts of continuous hydrological variables (2006, unknown): “Consider now the uniformity hypothesis: many goodness-of-fit tests for this hypothesis exist (D’Agostino and Stephens, 1986; Noceti et al., 2003).”
• Evaluating Rank Histograms Using Decompositions of the Chi-Square Test Statistic (2008, background): “Noceti et al. (2003) also examined the power of members of the Cramér–von Mises family of tests to detect various alternatives, although the context was different.”