induct
发表于 2025-3-26 23:41:31
How to Make Plausibility-Based Forecasting More Accurateing a uniform probability distribution for the plausibility level—is heuristic. It is therefore desirable to check whether this selection is optimal or whether a modified selection would like to a more accurate forecast. In this paper, we show that the uniform distribution does not always lead to (a
休战
发表于 2025-3-27 04:30:15
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大方不好
发表于 2025-3-27 08:23:29
Weighted Least Squares and Adaptive Least Squares: Further Empirical Evidencen application to two empirical data sets. Overall, ALS emerges as the winner: It achieves most or even all of the efficiency gains of WLS over OLS when WLS outperforms OLS, but it only has very limited downside risk compared to OLS when OLS outperforms WLS.
DIS
发表于 2025-3-27 09:39:17
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我不死扛
发表于 2025-3-27 14:02:07
Robustness in Forecasting Future Liabilities in Insurancetistical inference. In this paper, we propose two heavy-tailed distributions in the normal location-scale family and show that they are superior to the Gaussian distribution in the modelling of claim amount data from multiple lines of insurance business. Moreover, they also enable better forecasts o
indecipherable
发表于 2025-3-27 18:47:23
On Conditioning in Multidimensional Probabilistic Modelsand processing. The technique making computation with several hundred dimensional probability distribution possible was suggested by Lauritzen and Spiegelhalter. However, to employ it one has to transform a Bayesian network into a .. This is because decomposable models (or more precisely their build
精致
发表于 2025-3-28 01:36:11
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行为
发表于 2025-3-28 04:29:12
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背景
发表于 2025-3-28 09:02:21
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向下五度才偏
发表于 2025-3-28 11:40:25
International Yield Curve Prediction with Common Functional Principal Component Analysisethod that enables a comparison of the variation patterns across different economies with heterogeneous covariances. The dynamics of the international yield curves are further forecasted based on the data-driven common factors in an autoregression framework. For the 1-day ahead out-of-sample forecas