ENBIS 2021 Spring Meeting

Session

Process modelling

2.1.2

18 May 2021, 10:00

Online

Conveners

Process modelling

• Kristina Krebs (prognostica GmbH)

69. High-dimensional copula-based classification using truncation and thresholding

Mr Max-Carl Wachter (University of Wuerzburg)

18/05/2021, 10:00

Data Science in Process Industries

Bayes classifiers rest on maximising the joint conditional PDF of the feature vector under the class value. The usage of copulae is the most flexible way of fitting joint distributions to data. In recent years, the problem of applying copulae to high dimensions has been approached with Vine copulae. Nevertheless, the application to very high dimensions in the order of several thousands have...

70. Portfolio optimisation in very high dimension based on copula association modelling

Mr Philipp Haid (University of Wuerzburg)

18/05/2021, 10:20

Data Science in Process Industries

Portfolio optimisation requires insight into the joint distribution of the asset returns, in particular the association or dependence between the individual returns. Classical approaches use the covariance matrix for association modelling. However, the usage of copulae is the most flexible way of fitting joint distributions to data. In recent years, the problem of applying copulae to high...

81. High-purity processes GLR control charts for composite change-point scenarios

Caterina Rizzo (Dow Inc.)

18/05/2021, 10:40

Data Science in Process Industries

Generalized Likelihood Ratio (GLR)-based control charts for monitoring count processes have been proposed considering a variety of underlying dis- tributions and they are known to outperform the traditional control charts in effectively detecting a wide range of parameters’ shifts, while being relatively easy to design. In this study, generalized likelihood ratio tests for monitoring...