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AUEB-Stats Seminars 7/6/2024: "Response Modelling Approach to Robust Parameter Design Methodology Using Supersaturated Designs", by Krystallenia Drosou (Teaching Lecturer, NTUA) Forumgrstats

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AUEB-Stats Seminars 7/6/2024: "Response Modelling Approach to Robust Parameter Design Methodology Using Supersaturated Designs", by Krystallenia Drosou (Teaching Lecturer, NTUA) Forumgrstats
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AUEB-Stats Seminars 7/6/2024: "Response Modelling Approach to Robust Parameter Design Methodology Using Supersaturated Designs", by Krystallenia Drosou (Teaching Lecturer, NTUA) Empty AUEB-Stats Seminars 7/6/2024: "Response Modelling Approach to Robust Parameter Design Methodology Using Supersaturated Designs", by Krystallenia Drosou (Teaching Lecturer, NTUA)

Wed 5 Jun 2024 - 21:11
AUEB STATS SEMINARS 2024

Krystallenia Drosou
(Teaching Lecturer, NTUA)


Title: Response Modelling Approach to Robust Parameter Design Methodology Using Supersaturated Designs

Friday, 7/06/2024
13:00

Room T202, Troias Building

🔎 https://www.dept.aueb.gr/el/stat/events/response-modelling-approach-robust-parameter-design-methodology-using

ABSTRACT

In recent years, both robust parameter designs (RPDs) and supersaturated designs (SSDs) have attracted a great deal of attention. Robust parameter design methodology (RPDM) constitutes a statistical methodology that aims at reducing the performance variation of a system owing to hard to control variables while supersaturated designs (SSDs) constitute a large class of factorial designs which can be used for screening out the important factors from a large set of potentially active ones. This study considers a common sense of both fields. During the seminar, I will present a construction of an effective SSD along with an analysis method, in order to deal with the significant problem of RPDM. The proposed methodology applied in different models so as to show its effectiveness in many different scenarios, assuming both first and second- order models in a sense of a response surface design. In this talk, I will focus on two illustrative examples as well as numerous numerical experiments for plenty cases where the results imply that the proposed method is highly effective for identifying the important effects under the assumption of effect sparsity.

AUEB-Stats Seminars 7/6/2024: "Response Modelling Approach to Robust Parameter Design Methodology Using Supersaturated Designs", by Krystallenia Drosou (Teaching Lecturer, NTUA) 1717334474764?e=1720656000&v=beta&t=rfWGflk8cXb1_gmaMszy0XQfCg5nX8QP-RZAbGseRUU
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