A method for medical screening is adapted to differential item functioning (DIF). Its essential elements are explicit declarations of the level of DIF that is acceptable and of the loss function that quantifies the consequences of the two kinds of inappropriate classification of an item. Instead...

Evaluation of forecast optimality in economics and finance has almost exclusively been conducted on the assumption of mean squared error loss under which forecasts should be unbiased and forecast errors serially uncorrelated at the single period horizon with increasing variance as the forecast...

The scientific evaluation methodology for the forecast accuracy of wind power forecasting models is an important issue in the domain of wind power forecasting. However, traditional forecast evaluation criteria, such as Mean Squared Error (MSE) and Mean Absolute Error (MAE), have limitations in...

Working with micro-founded loss functions to derive and analyse optimal policy ensures consistency with the model used and overcomes the misleading prescriptions that result from using exogenous ad hoc loss functions. However, when allowance is made for the fact that different theories of...

Acceptance sampling has been one of practical tools for quality assurance applications, which provide a general rule to the producer and the consumer for product acceptance determination. It has been shown that variables sampling plans requires less sampling compared with attributes sampling...

Loss functions play a central role in the theory and practice of forecasting. If the loss function is quadratic, the mean of the predictive distribution is the unique optimal point predictor. If the loss is symmetric piecewise linear, any median is an optimal point forecast. Quantiles arise as...

This paper focuses on Bayesian shrinkage methods for covariance matrix estimation. We examine posterior properties and frequentist risks of Bayesian estimators based on new hierarchical inverse-Wishart priors. More precisely, we give the conditions for the existence of the posterior...

Working with micro-founded loss functions to derive and analyse optimal policy ensures consistency with the model used and overcomes the misleading prescriptions that result from using exogenous ad hoc loss functions. However, when allowance is made for the fact that different theories of...

We propose a new approach to evaluating the usefulness of a set of forecasts, based on the use of a discrete loss function de…ned on the space of data and forecasts. Exist- ing procedures for such an evaluation either do not allow for formal testing, or use tests statistics based just on the...

Evaluating Value at Risk (VaR) methods of predictive accuracy in an objective and effective framework is important for both efficient capital allocation and loss prediction. From this reasons, finding an adequate method of estimating and backtesting is crucial for both the regulators and the...