%0 Journal Article %1 gneiting_comparing_2011 %A Gneiting, Tilmann %A Ranjan, Roopesh %D 2011 %J Journal of Business & Economic Statistics %K brier model score, selection %N 3 %P 411--422 %R 10.1198/jbes.2010.08110 %T Comparing density forecasts using threshold- and quantile-weighted scoring rules %U http://www.stat.washington.edu/research/reports/2008/tr533.pdf %V 29 %X We propose a method for comparing density forecasts that is based on weighted versions of the continuous ranked probability score. The weighting emphasizes regions of interest, such as the tails or the center of a variable’s range, while retaining propriety, as opposed to a recently developed weighted likelihood ratio test, which can be hedged. Threshold- and quantile-based decompositions of the continuous ranked probability score can be illustrated graphically and provide insight into the strengths and deficiencies of a forecasting method. We illustrate the use of the test and graphical tools in case studies on the Bank of England’s density forecasts of quarterly inflation rates in the United Kingdom, and probabilistic predictions of wind resources in the Pacific Northwest.

@article{gneiting_comparing_2011, abstract = {We propose a method for comparing density forecasts that is based on weighted versions of the continuous ranked probability score. The weighting emphasizes regions of interest, such as the tails or the center of a variable’s range, while retaining propriety, as opposed to a recently developed weighted likelihood ratio test, which can be hedged. Threshold- and quantile-based decompositions of the continuous ranked probability score can be illustrated graphically and provide insight into the strengths and deficiencies of a forecasting method. We illustrate the use of the test and graphical tools in case studies on the Bank of England’s density forecasts of quarterly inflation rates in the United Kingdom, and probabilistic predictions of wind resources in the Pacific Northwest.}, added-at = {2017-01-09T13:57:26.000+0100}, author = {Gneiting, Tilmann and Ranjan, Roopesh}, biburl = {https://www.bibsonomy.org/bibtex/2367027a2fd150dbab0264e838129f926/yourwelcome}, doi = {10.1198/jbes.2010.08110}, interhash = {11af92ceb9afcea9e09b01007218ef05}, intrahash = {367027a2fd150dbab0264e838129f926}, issn = {0735-0015, 1537-2707}, journal = {Journal of Business \& Economic Statistics}, keywords = {brier model score, selection}, month = jul, number = 3, pages = {411--422}, timestamp = {2017-01-09T14:01:11.000+0100}, title = {Comparing density forecasts using threshold- and quantile-weighted scoring rules}, url = {http://www.stat.washington.edu/research/reports/2008/tr533.pdf}, urldate = {2012-12-06}, volume = 29, year = 2011 }