Artikel

Shrinkage simplex-centroid designs for a quadratic mixture model

A simplex-centroid design for q mixture components comprises of all possible subsets of the q components, present in equal proportions. The design does not contain full mixture blends except the overall centroid. In real-life situations, all mixture blends comprise of at least a minimum proportion of each component. Here, we introduce simplex-centroid designs which contain complete blends but with some loss in D-efficiency and stability in G-efficiency. We call such designs as shrinkage simplex-centroid designs. Furthermore, we use the proposed designs to generate component-amount designs by their projection.

Language: Englisch

Bibliographic citation: Journal: Journal of Industrial Engineering International ; ISSN: 2251-712X ; Volume: 14 ; Year: 2018 ; Issue: 1 ; Pages: 87-93 ; Heidelberg: Springer

Classification: Management

Subject: Mixture experiment
Simplex-centroid design
D-optimality
G-optimality

Event: Geistige Schöpfung

(who): Hasan, Taha
Ali, Sajid
Ahmed, Munir

Event: Veröffentlichung

(who): Springer

(where): Heidelberg

(when): 2018

DOI: doi:10.1007/s40092-017-0210-1

Handle: http://hdl.handle.net/10419/195593

Last update: 10.03.2025, 11:41 AM CET

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Artikel

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Hasan, Taha
Ali, Sajid
Ahmed, Munir
Springer

Time of origin

2018

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Shrinkage simplex-centroid designs for a quadratic mixture model

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Shrinkage simplex-centroid designs for a quadratic mixture model

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Other Objects (12)

Shrinkage simplex-centroid designs for a quadratic mixture model

Quadratic shrinkage for large covariance matrices

Quadratic shrinkage for large covariance matrices

Kiefer ordering of simplex designs for first- and second-degree mixture models

Kiefer ordering of simplex designs for second-degree mixture models with four or more ingredients

Bayesian shrinkage in mixture-of-experts models: identifying robust determinants of class membership

Optimal designs for quadratic regression

Use of Quadratic Model for Modelling of Fly Ash-Water Mixture

A Global Optimality Criterion for Nonconvex Quadratic Programming over a Simplex

On Reverse Shrinkage Effects and Shrinkage Overshoot

Some Heuristics and Test Problems for Nonconvex Quadratic Programming over a Simplex

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Shrinkage simplex-centroid designs for a quadratic mixture model

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Quadratic shrinkage for large covariance matrices

Kiefer ordering of simplex designs for first- and second-degree mixture models

Kiefer ordering of simplex designs for second-degree mixture models with four or more ingredients

Bayesian shrinkage in mixture-of-experts models: identifying robust determinants of class membership

Optimal designs for quadratic regression

Use of Quadratic Model for Modelling of Fly Ash-Water Mixture

A Global Optimality Criterion for Nonconvex Quadratic Programming over a Simplex

On Reverse Shrinkage Effects and Shrinkage Overshoot

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Shrinkage simplex-centroid designs for a quadratic mixture model

Quadratic shrinkage for large covariance matrices

Quadratic shrinkage for large covariance matrices

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Kiefer ordering of simplex designs for second-degree mixture models with four or more ingredients

Bayesian shrinkage in mixture-of-experts models: identifying robust determinants of class membership

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Use of Quadratic Model for Modelling of Fly Ash-Water Mixture

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