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Titlebook: Studies in Theoretical and Applied Statistics; SIS 2021, Pisa, Ital Nicola Salvati,Cira Perna,Raymond Chambers Conference proceedings 2022

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樓主: CILIA
11#
發(fā)表于 2025-3-23 12:52:03 | 只看該作者
A Composite Index of Economic Well-Being for the European Union Countries,e focus on the Economic Well-being domain seems essential around the last serious economic crisis. The use of an innovative composite index can help to measure the multidimensional phenomenon and monitor the situation at European level.
12#
發(fā)表于 2025-3-23 17:32:16 | 只看該作者
,A Dynamic Power Prior for?Bayesian Non-inferiority Trials,as long as the past and the current experiments are sufficiently homogeneous, historical data may be useful to reserve resources to the new therapy’s arm and to improve accuracy of inference. In this article we propose a Bayesian method for exploiting historical information based on a dynamic power
13#
發(fā)表于 2025-3-23 21:32:50 | 只看該作者
,A Graphical Approach for?the?Selection of?the?Number of?Clusters in?the?Spectral Clustering Algorition of the optimal number of clusters in the spectral clustering algorithm. To this end, we propose a multi-graphic method that takes into account geometric characteristics derived from the similarity matrix and from the Laplacian embedding among data. Our approach is supported by some mathematical
14#
發(fā)表于 2025-3-23 22:20:36 | 只看該作者
,A Higher-Order PLS-SEM Approach to?Evaluate Football Players’ Performance,ata-driven approach. In this context, we pay our attention on football (e.g. soccer in USA); by this project we aim to give a new approach and a statistical support in the evaluation of football players’ performance provided from the EA Sports experts and available on Kaggle in the free KES dataset.
15#
發(fā)表于 2025-3-24 03:19:32 | 只看該作者
16#
發(fā)表于 2025-3-24 06:31:39 | 只看該作者
17#
發(fā)表于 2025-3-24 11:07:52 | 只看該作者
18#
發(fā)表于 2025-3-24 17:40:12 | 只看該作者
19#
發(fā)表于 2025-3-24 20:17:30 | 只看該作者
20#
發(fā)表于 2025-3-25 02:51:42 | 只看該作者
,Can the?Compositional Nature of?Compositional Data Be Ignored by?Using Deep Learning Approaches?,or example, one can show that Pearson correlations applied to compositional data are biased to be negative. Moreover, almost all statistical methods lead to biased estimates when applied to compositional data. One way out is to analyze data after representing them in log-ratio coordinates. However,
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