T‐optimum designs for discrimination between two multiresponse dynamic models

By Dariusz Ucinski, Barbara Bogacka. 2005

104 citations recorded by the source corpus.

Subfields: Analytical Chemistry, Computational Theory and Mathematics, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/f0d4460aeef83fb80a5562e1ac915c68e66c3439

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Analytical Chemistry

1. J. López–Fidalgo
2. Holger Dette
3. Douglas P. Wiens
4. Paula Camelia Trandafir
5. Chiara Tommasi

In Computational Theory and Mathematics

1. Douglas P. Wiens
2. J. López–Fidalgo
3. Holger Dette
4. Paula Camelia Trandafir
5. Chiara Tommasi
6. Luzia A. Trinca
7. Steven G. Gilmour

In Management Science and Operations Research

1. Douglas P. Wiens
2. J. López–Fidalgo
3. Holger Dette
4. Paula Camelia Trandafir
5. Chiara Tommasi
6. Masashi Sugiyama
7. Luzia A. Trinca
8. Steven G. Gilmour

Citations in the corpus

• Optimal discrimination designs (2009, background): “This optimality criterion is meanwhile called T -criterion in the statistical literature and has been considered by several authors, mostly in the context of regression models (see, e.g., Ucinski and Bogacka [39], López-Fidalgo, Tommasi and Trandafir [24] or Waterhouse et al. [40] for some recent r”
• Robust discrimination designs (2009, background): “Uciński and Bogacka (2005) considered extensions to multiresponse models.”
• An optimal experimental design criterion for discriminating between non‐normal models (2007, methodology): “For a generalization of this criterion for multiresponse models, see Uciński and Bogacka (2005).”