This is a comment on Mitchell and Wallis (2011) which in turn is a critical reaction to Gneiting et al. (2007). The comment discusses the notion of forecast calibration, the advantage of using scoring rules, the “sharpness” principle and a general approach to testing calibration. The aim is to show how a more general and explicitly stated framework can provide further insights into the theory and practice of of probabilistic forecasting
Predictions are often probabilities; e.g., a prediction could be for precipitation tomorrow, but wit...
We respond to Tetlock et al. (2022) showing 1) how expert judgment fails to reflect tail risk, 2) th...
We address the calibration constraint of probability forecasting. We propose a generic method for re...
This is a comment on Mitchell and Wallis (2011) which in turn is a critical reaction to Gneiting et ...
Schervish (1985b) showed that every forecasting system is noncalibrated for uncountably many data se...
The paper explores probability theory foundations behind evaluation of probabilistic forecasts. The ...
This thesis consists in three essays on predictive distributions, in particular their combination, c...
This work is concerned with evaluating the performance of forecasts. Various types of forecast are s...
In a recent article Gneiting, Balabdaoui and Raftery (JRSSB, 2007) propose the criterion of sharpnes...
There are three main ways in which judgmental predictions are expressed: point forecasts; interval f...
The paper explores the relationship between various orderings among probability forecasts that have ...
We consider whether survey respondents' probability distributions, reported as histograms, provide r...
This paper reviews current density forecast evaluation procedures, and considers a proposal that suc...
Summary: This paper reviews current density forecast evaluation procedures, and considers a recent ...
Predictability varies. In geophysical systems, and related mathematical dynamical systems, variation...
Predictions are often probabilities; e.g., a prediction could be for precipitation tomorrow, but wit...
We respond to Tetlock et al. (2022) showing 1) how expert judgment fails to reflect tail risk, 2) th...
We address the calibration constraint of probability forecasting. We propose a generic method for re...
This is a comment on Mitchell and Wallis (2011) which in turn is a critical reaction to Gneiting et ...
Schervish (1985b) showed that every forecasting system is noncalibrated for uncountably many data se...
The paper explores probability theory foundations behind evaluation of probabilistic forecasts. The ...
This thesis consists in three essays on predictive distributions, in particular their combination, c...
This work is concerned with evaluating the performance of forecasts. Various types of forecast are s...
In a recent article Gneiting, Balabdaoui and Raftery (JRSSB, 2007) propose the criterion of sharpnes...
There are three main ways in which judgmental predictions are expressed: point forecasts; interval f...
The paper explores the relationship between various orderings among probability forecasts that have ...
We consider whether survey respondents' probability distributions, reported as histograms, provide r...
This paper reviews current density forecast evaluation procedures, and considers a proposal that suc...
Summary: This paper reviews current density forecast evaluation procedures, and considers a recent ...
Predictability varies. In geophysical systems, and related mathematical dynamical systems, variation...
Predictions are often probabilities; e.g., a prediction could be for precipitation tomorrow, but wit...
We respond to Tetlock et al. (2022) showing 1) how expert judgment fails to reflect tail risk, 2) th...
We address the calibration constraint of probability forecasting. We propose a generic method for re...