In this paper, we studied estimators based on an interval shrinkage with equal weights point shrinkage estimators for all individual target points ¯θ ∈ (θ0,θ1) for exponentially distributed observations in the presence of outliers drawn from a uniform distribution. Estimators...

We develop metrics based on Shapley values for interpreting time-series forecasting models, including "black-box" models from machine learning. Our metrics are model agnostic, so that they are applicable to any model (linear or nonlinear, parametric or nonparametric). Two of the metrics,...

In this paper, we studied estimators based on an interval shrinkage with equal weights point shrinkage estimators for all individual target points ¯θ ∈ (θ0,θ1) for exponentially distributed observations in the presence of outliers drawn from a uniform distribution. Estimators obtained from...

We develop metrics based on Shapley values for interpreting time-series forecasting models, including "black-box" models from machine learning. Our metrics are model agnostic, so that they are applicable to any model (linear or nonlinear, parametric or nonparametric). Two of the metrics,...